WO2021243529A1 - 一种波达角aoa估计方法和装置 - Google Patents
一种波达角aoa估计方法和装置 Download PDFInfo
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- WO2021243529A1 WO2021243529A1 PCT/CN2020/093812 CN2020093812W WO2021243529A1 WO 2021243529 A1 WO2021243529 A1 WO 2021243529A1 CN 2020093812 W CN2020093812 W CN 2020093812W WO 2021243529 A1 WO2021243529 A1 WO 2021243529A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- This application relates to the field of radar communication technology, and in particular to an AOA estimation method and device for the angle of arrival.
- Vehicle-mounted radar is an indispensable sensor in the automatic driving system.
- the vehicle-mounted radar can provide obstacle detection for the vehicle.
- Vehicle-mounted radars put forward higher requirements for signal processing, requiring lower computational complexity to meet the real-time performance of the system, and high enough accuracy to ensure the reliability of the system.
- the angle of arrival (AOA) estimation is an important part of the radar signal processing process.
- AOA estimation algorithms include two major categories:
- the first is an algorithm that can calculate a closed-form solution represented by the estimation of signal parameters via rotational invariance technology (ESPRIT) and root-multiple classification (root-MUSIC).
- ESPRIT rotational invariance technology
- root-MUSIC root-multiple classification
- the spatial spectrum search algorithm first needs to calculate the spatial spectrum, and determine the AOA estimation value by looking for the spatial spectrum peak. Since the spatial angle is a continuous variable, the continuous spatial angle needs to be discretized when calculating the spatial spectrum, and the spatial spectrum is obtained by calculating the amplitude at each discrete point.
- this type of algorithm has the following two shortcomings: one is that the dense meshing of the spatial spectrum may increase the number of space points and increase the computational complexity; the other is that the real spatial angle may not necessarily fall within the division. On the grid, there will be quantization errors that make it difficult to obtain the best estimate.
- the present application provides a method and device for AOA estimation of the angle of arrival, which are used to reduce the calculation amount of the angle of arrival estimation and improve the accuracy of the estimated value of the arrival angle.
- this application provides an AOA estimation method for the angle of arrival, which can be executed by a processing device or by other devices similar to the processing device.
- the processing device may use the echo signal and a preset first spatial grid to establish the first spatial spectrum. It is also possible to perform target detection in the established first space spectrum to obtain a spectrum peak in the first space. According to the first spatial grid and the detected spectral peak, the first discrete error of the spectral peak in the first spatial grid is calculated. The processing device may correct the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain the estimated value of the arrival angle of the echo signal.
- the discrete error of the spectral peak corresponding to the point in the spatial grid in the spatial spectrum can be calculated, and the point corresponding to the spectral peak in the spatial grid can be corrected according to the discrete error, which can improve the accuracy of the estimated value of arrival angle .
- the step size of the first spatial grid is a first value.
- the first value here may be a value greater than or equal to an integer multiple of the resolution of the radar system.
- the step size can be 5 times, 8 times, etc., the resolution of the radar system.
- the radar system is a radar system that transmits a radar signal corresponding to the echo signal. For example, if the radar system L emits a radar signal, which is reflected by the array A to form an echo signal, the radar signal corresponding to the echo signal is the radar signal emitted by the radar system L.
- a spatial grid with a larger step size can be used, which can reduce the amount of calculation when estimating the arrival angle, and combine the calculated discrete error to correct the point corresponding to the spectral peak in the spatial grid.
- the accuracy of the estimated value of the arrival angle can be improved while reducing the amount of calculation.
- the processing device may To determine the steering vector of the echo signal, the steering vector may be expanded by Taylor series at the point corresponding to the spectral peak in the first spatial grid. The processing device may obtain the first dispersion error of the spectral peak according to the expanded steering vector.
- the Taylor series expansion can be performed on the corresponding points of the steering vector in the first spatial grid, so that the discrete error approaches a convergent value, and the discrete error can be calculated more easily.
- the first discrete error ⁇ k may satisfy the following expression:
- the dispersion error of the corresponding point of the spectral peak in the spatial grid can be calculated according to the above formula, so as to correct the spatial grid, and the accuracy of the estimated value of the arrival angle can be improved.
- the processing device may correct the corresponding point of the spectral peak in the second spatial grid according to the second discrete error to obtain the estimated value of the arrival angle of the echo signal.
- the processing device can also perform the above operations cyclically. For example, after the second discrete error is calculated, the point corresponding to the spectral peak in the second spatial grid can be corrected again according to the second discrete error to obtain a new According to the new second spatial grid and the spectral peak, a new second discrete error can be calculated.
- the processing device may end the above-mentioned loop operation when the iteration condition is satisfied, and correct the corresponding point of the spectral peak in the second spatial grid according to the second discrete error obtained in the last iteration, and finally obtain the echo The estimated value of the angle of arrival of the signal.
- a more accurate estimate of the arrival angle can be obtained according to the second discrete error, and the discrete error of the points corresponding to the spectral peaks in the spatial grid can be reduced multiple times according to the above-mentioned cyclic operation to reduce the spectral peaks and the real space.
- the error between the angles can improve the accuracy of the estimated value of the arrival angle.
- the spectral peaks are in the first spatial grid.
- the points corresponding to the spectral peaks and the target points are used as spectral peaks in the first spatial spectrum.
- the points of the spatial grid corresponding to the spectral peaks can be split, which can avoid the loss of the target, that is, the real spatial angle.
- the echo signal may be processed to obtain a range-doppler diagram (range-doppler diagram). map, RDmap).
- the processing device may also use the first cluster data in the RDmap and the first spatial grid to establish the first spatial spectrum.
- the first cluster of data here can be any cluster of data in the multiple clusters of data in the RDmap, or it can be a cluster of data composed of points with a high signal-to-noise ratio in the RDmap data.
- the echo signal can be processed to obtain RDmap data, a point with a high signal-to-noise ratio can be selected in the RDmap data, and a preset first spatial grid can be used to establish a first spatial spectrum.
- a point with a high signal-to-noise ratio can be selected in the RDmap data, and a preset first spatial grid can be used to establish a first spatial spectrum.
- using points with a high signal-to-noise ratio to establish a spatial spectrum can easily detect the spectrum peaks.
- the processing device may also correct the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain a third spatial grid. And it is also possible to use other data in the RDmap data except the first cluster data and the third spatial grid to establish a second spatial spectrum, and calculate the data corresponding to the other data except the first cluster data The estimated value of the arrival angle of the echo signal.
- the processing device uses the first cluster data in the RDmap and the first spatial grid to establish the first spatial spectrum.
- the spatial grid that has been corrected according to the first discrete error can be reused, which can further reduce the complexity of the calculation.
- an embodiment of the present application also provides an AOA estimation device for the angle of arrival, which can be used to perform the operations in the first aspect and any possible implementation of the first aspect.
- the device for estimating the angle of arrival AOA may include modules or units for performing the above-mentioned first aspect or any possible implementation of the first aspect.
- it includes a communication unit and a processing unit.
- an embodiment of the present application also provides an AOA estimation system for the angle of arrival, which may include the above-mentioned processing device and a radar system.
- the embodiments of the present application provide a chip system, including a processor, and optionally a memory; where the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the The communication device of the chip system executes the foregoing first aspect or any method in any possible implementation manner of the first aspect.
- the embodiments of the present application provide a computer program product, including computer program code.
- the computer program code is executed by a communication unit, a processing unit or a transceiver, or a processor of a communication device, the communication device can execute the foregoing Any method of one aspect or any possible implementation of the first aspect.
- the embodiments of the present application provide a computer-readable storage medium, and the computer-readable storage medium stores a program, and the program causes the communication device to execute the first aspect or any of the possible implementation manners of the first aspect. method.
- FIG. 1 is a schematic diagram of a radar system provided by this application.
- Figure 2 is a schematic diagram of an application scenario provided by an embodiment of the application
- FIG. 3 is one of the exemplary flowcharts of a method for estimating the angle of arrival provided by an embodiment of the application;
- FIG. 4 is a schematic diagram of an echo signal arrangement method provided by an embodiment of the application.
- FIG. 5 is a schematic diagram of an RDmap of an echo signal provided by an embodiment of this application.
- FIG. 6 is one of the schematic diagrams of the spatial grid provided by an embodiment of this application.
- FIG. 7 is one of the schematic diagrams of the spatial grid provided by an embodiment of this application.
- FIG. 8 is one of the schematic diagrams of the spatial grid provided by an embodiment of this application.
- FIG. 9 is a schematic diagram of the relationship between the number of cycles and the discrete error provided by an embodiment of the application.
- FIG. 10 is one of the exemplary flowcharts of a method for estimating the angle of arrival provided by an embodiment of the application.
- FIG. 11 is one of the schematic diagrams of a processing device provided by an embodiment of this application.
- FIG. 12 is one of the schematic diagrams of a processing device provided by an embodiment of this application.
- AOA Angle of arrival
- ASE angle spectrum estimation
- DOA direction of arrival
- Echo signal means that after the signal is reflected by the reflector, a part of the energy is absorbed by the reflector, and the original signal with attenuation and delay is generated, which is superimposed on the original signal path.
- Spatial spectrum refers to a graph showing the energy distribution of the sampled signal in various directions in space.
- the steering vector is a vector indicating the direction of the signal, and is the response of all the elements of the array antenna to a source with energy.
- a multiple-input multiple output (MIMO) radar system may include an antenna array 101, a monolithic microwave integrated circuit (monolithic microwave integrated circuit, MMIC) 102, and a processing unit 103.
- the antenna array 101 may include multiple transmitting antennas and multiple receiving antennas.
- the monolithic microwave integrated circuit 102 is used to generate radar signals, and then the radar signals are sent out through the antenna array 101.
- the radar signal includes multiple chirp signals. After the radar signal is sent out, it is reflected by one or more targets to form an echo signal, and the echo signal is received by the receiving antenna.
- the single-chip microwave integrated circuit 102 is also used to perform processing such as transformation and sampling on the echo signal received by the antenna array 101, and to transmit the processed echo signal to the processing unit 103.
- the processing unit 103 is used to perform Fast Fourier Transformation (FFT), signal processing and other operations on the echo signal, so as to determine the distance, speed, azimuth angle and other information of the target according to the received echo signal.
- the processing unit 103 may be a microprocessor (microcontroller unit, MCU), a central processing unit (CPU), a digital signal processor (digital signal processor, DSP), and a field programmable gate array (field-programmable gate array).
- Programmable gate array, FPGA dedicated accelerators and other devices with processing functions.
- the radar system shown in FIG. 1 may also include an electronic control unit (ECU) 104, which is used to control the vehicle according to the target distance, speed, azimuth and other information processed by the processing unit 103, such as determining The route of the vehicle, the speed of the vehicle, etc.
- ECU electronice control unit
- the processing device in the embodiment of the present application may be implemented by the foregoing processing unit 103.
- the entire radar system may include multiple radio frequency chip cascades.
- the transmitting antenna array and the receiving antenna array are obtained by cascading multiple MIMO, and are connected to the data output by the analog digital converter (analog digital converter, ADC) channel through the interface.
- ADC analog digital converter
- MMIC and DSP can be integrated in one chip, which is called System on Chip (SOC).
- the MMIC and ADC, and the processing unit 103 can be integrated into one chip to form an SOC.
- the entire vehicle may be equipped with one or more radar systems, which are connected to the central processing unit through the on-board bus.
- the central processor controls one or more on-board sensors, including one or more millimeter wave radar sensors.
- the MIMO radar system shown in Figure 1 can be applied to vehicles with autonomous driving functions.
- FIG. 2 is a functional block diagram of a vehicle 200 with an automatic driving function provided in an embodiment of the present application.
- the vehicle 200 is configured in a fully or partially autonomous driving mode.
- the vehicle 200 can control itself at the same time when it is in the automatic driving mode, and can determine the current state of the vehicle and its surrounding environment through human operations, determine the possible behavior of at least one other vehicle in the surrounding environment, and determine that the other vehicle performs The likelihood of the possible behavior corresponds to the confidence level, and the vehicle 200 is controlled based on the determined information.
- the vehicle 200 may be placed to operate without human interaction.
- the vehicle 200 may include various subsystems, such as a travel system 202, a sensor system 204, a control system 206, one or more peripheral devices 208 and a power supply 210, a computer system 212, and a user interface 216.
- the vehicle 200 may include more or fewer subsystems, and each subsystem may include multiple elements.
- each subsystem and element of the vehicle 200 may be interconnected by wire or wirelessly.
- the travel system 202 may include components that provide power movement for the vehicle 200.
- the travel system 202 may include an engine 218, an energy source 219, a transmission 220, and wheels/tires 221.
- the engine 218 may be an internal combustion engine, an electric motor, an air compression engine, or a combination of other types of engines, such as a hybrid engine composed of a gas oil engine and an electric motor, or a hybrid engine composed of an internal combustion engine and an air compression engine.
- the engine 218 is used to convert the energy source 219 into mechanical energy.
- Examples of energy sources 219 include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electricity.
- the energy source 219 may also provide energy for other systems of the vehicle 200.
- the transmission 220 can transmit the mechanical power from the engine 218 to the wheels 221.
- the transmission 220 may include a gearbox, a differential, and a drive shaft.
- the transmission device 220 may also include other devices, such as a clutch.
- the drive shaft may include one or more shafts that can be coupled to one or more wheels 221.
- the sensor system 204 may include several sensors that sense information about the environment around the vehicle 200.
- the sensor system 204 may include a positioning system 222 (the positioning system may be a global positioning system (GPS) system, a Beidou system or other positioning systems), an inertial measurement unit (IMU) 224, Radar 226, laser rangefinder 228, and camera 230.
- the sensor system 204 may also include sensors of the internal system of the monitored vehicle 200 (for example, an in-vehicle air quality monitor, a fuel gauge, an oil temperature gauge, etc.). Sensor data from one or more of these sensors can be used to detect objects and their corresponding characteristics (position, shape, direction, speed, etc.). Such detection and identification are key functions for the safe operation of the vehicle 200.
- the positioning system 222 can be used to estimate the geographic location of the vehicle 200.
- the IMU 224 is used to sense changes in the position and orientation of the vehicle 200 based on inertial acceleration.
- the IMU 224 may be a combination of an accelerometer and a gyroscope.
- the radar 226 may use radio signals to sense targets in the surrounding environment of the vehicle 200. In some embodiments, in addition to sensing the target, the radar 226 may also be used to sense the speed and/or heading of the target. In a specific example, the radar 226 may be implemented using the MIMO radar system shown in FIG. 1.
- the laser rangefinder 228 can use laser light to sense a target in the environment where the vehicle 100 is located.
- the laser rangefinder 228 may include one or more laser sources, laser scanners, and one or more detectors, as well as other system components.
- the camera 230 may be used to capture multiple images of the surrounding environment of the vehicle 200.
- the camera 230 may be a still camera or a video camera.
- the control system 206 controls the operation of the vehicle 200 and its components.
- the control system 206 may include various components, including a steering system 232, a throttle 234, a braking unit 236, a sensor fusion algorithm 238, a computer vision system 240, a route control system 242, and an obstacle avoidance system 244.
- the steering system 232 is operable to adjust the forward direction of the vehicle 200.
- it may be a steering wheel system.
- the throttle 234 is used to control the operating speed of the engine 218 and thereby control the speed of the vehicle 200.
- the braking unit 236 is used to control the vehicle 200 to decelerate.
- the braking unit 236 may use friction to slow down the wheels 221.
- the braking unit 236 may convert the kinetic energy of the wheels 221 into electric current.
- the braking unit 236 may also take other forms to slow down the rotation speed of the wheels 221 so as to control the speed of the vehicle 200.
- the computer vision system 240 may be operable to process and analyze the images captured by the camera 230 in order to identify objects and/or features in the surrounding environment of the vehicle 200.
- the targets and/or features may include traffic signals, road boundaries, and obstacles.
- the computer vision system 240 may use target recognition algorithms, structure from motion (SFM) algorithms, video tracking, and other computer vision technologies.
- the computer vision system 240 may be used to map the environment, track targets, estimate the speed of targets, and so on.
- the route control system 242 is used to determine the travel route of the vehicle 200.
- the route control system 142 may combine data from the sensor 238, the GPS 222, and one or more predetermined maps to determine the driving route for the vehicle 200.
- the obstacle avoidance system 244 is used to identify, evaluate and avoid or otherwise cross over potential obstacles in the environment of the vehicle 200.
- control system 206 may additionally or alternatively include components other than those shown and described. Alternatively, a part of the components shown above may be reduced.
- the vehicle 200 interacts with external sensors, other vehicles, other computer systems, or users through peripheral devices 208.
- the peripheral device 208 may include a wireless communication system 246, an onboard computer 248, a microphone 250, and/or a speaker 252.
- the peripheral device 208 provides a means for the user of the vehicle 200 to interact with the user interface 216.
- the onboard computer 248 can provide information to the user of the vehicle 200.
- the user interface 216 can also operate the onboard computer 248 to receive user input.
- the on-board computer 248 can be operated via a touch screen.
- the peripheral device 208 may provide a means for the vehicle 200 to communicate with other devices located in the vehicle.
- the microphone 250 may receive audio (eg, voice commands or other audio input) from a user of the vehicle 200.
- the speaker 252 may output audio to the user of the vehicle 200.
- the wireless communication system 246 may wirelessly communicate with one or more devices directly or via a communication network.
- the wireless communication system 246 can use 3G cellular communication, such as code division multiple access (CDMA), EVD0, global system for mobile communications (GSM)/general packet radio service technology (general packet radio service, GPRS), or 4G cellular communication, such as long term evolution (LTE), or 5G cellular communication.
- the wireless communication system 246 may use WiFi to communicate with a wireless local area network (WLAN).
- the wireless communication system 246 can directly communicate with the device using an infrared link, Bluetooth, or ZigBee.
- Other wireless protocols such as various vehicle communication systems.
- the wireless communication system 246 may include one or more dedicated short-range communications (DSRC) devices. These devices may include vehicles and/or roadside stations. Public and/or private data communications.
- DSRC dedicated short-range communications
- the power supply 210 may provide power to various components of the vehicle 200.
- the power source 210 may be a rechargeable lithium ion or lead-acid battery.
- One or more battery packs of such batteries may be configured as a power source to provide power to various components of the vehicle 200.
- the power source 210 and the energy source 219 may be implemented together, such as in some all-electric vehicles.
- the computer system 212 may include at least one processor 223 that executes instructions 225 stored in a non-transitory computer readable medium such as the memory 224.
- the computer system 212 may also be multiple computing devices that control individual components or subsystems of the vehicle 200 in a distributed manner.
- the processor 223 may be any conventional processor, such as a commercially available central processing unit (CPU). Alternatively, the processor may be a dedicated device such as an application specific integrated circuit (ASIC) or other hardware-based processor.
- FIG. 2 functionally illustrates the processor, memory, and other elements of the computer 210 in the same block, those of ordinary skill in the art should understand that the processor, computer, or memory may actually include Multiple processors, computers, or memories stored in the same physical enclosure.
- the memory may be a hard disk drive or other storage medium located in a housing other than the computer 210. Therefore, a reference to a processor or computer will be understood to include a reference to a collection of processors or computers or memories that may or may not operate in parallel. Rather than using a single processor to perform the steps described here, some components such as steering components and deceleration components may each have its own processor that only performs calculations related to component-specific functions .
- the processor may be located away from the vehicle and wirelessly communicate with the vehicle.
- some of the processes described herein are executed on a processor disposed in the vehicle and others are executed by a remote processor, including taking the necessary steps to perform a single manipulation.
- the memory 224 may contain instructions 225 (eg, program logic), which may be executed by the processor 223 to perform various functions of the vehicle 200, including those functions described above.
- the memory 214 may also contain additional instructions, including those for sending data to, receiving data from, interacting with, and/or controlling one or more of the traveling system 202, the sensor system 204, the control system 206, and the peripheral device 208. instruction.
- the memory 224 may also store data, such as road maps, route information, the location, direction, and speed of the vehicle, and other such vehicle data, as well as other information. Such information may be used by the vehicle 200 and the computer system 212 during operation of the vehicle 200 in autonomous, semi-autonomous, and/or manual modes.
- the user interface 216 is used to provide information to or receive information from a user of the vehicle 200.
- the user interface 216 may include one or more input/output devices in the set of peripheral devices 208, such as a wireless communication system 246, a car computer 248, a microphone 250, and a speaker 252.
- the computer system 212 may control the functions of the vehicle 200 based on inputs received from various subsystems (for example, the travel system 202, the sensor system 204, and the control system 206) and from the user interface 216.
- the computer system 212 may utilize input from the control system 206 in order to control the steering unit 232 to avoid obstacles detected by the sensor system 204 and the obstacle avoidance system 244.
- the computer system 212 is operable to provide control of many aspects of the vehicle 200 and its subsystems.
- one or more of these components described above may be installed or associated with the vehicle 200 separately.
- the storage 224 may be partially or completely separated from the vehicle 200.
- the aforementioned components may be communicatively coupled together in a wired and/or wireless manner.
- FIG. 2 should not be construed as a limitation to the embodiments of the present application.
- An autonomous vehicle traveling on a road can recognize targets in its surrounding environment to determine the adjustment to the current speed.
- the target may be other vehicles, traffic control equipment, or other types of targets.
- each identified target can be considered independently, and based on the respective characteristics of the target, such as its current speed, acceleration, distance from the vehicle, etc., can be used to determine the speed to be adjusted by the autonomous vehicle.
- the self-driving car 200 or the computing device associated with the self-driving vehicle 200 may be based on the characteristics of the identified target and the state of the surrounding environment (E.g., traffic, rain, ice on the road, etc.) to predict the behavior of the identified target.
- each identified target depends on each other's behavior, so all the identified targets can also be considered together to predict the behavior of a single identified target.
- the vehicle 200 can adjust its speed based on the predicted behavior of the identified target.
- an autonomous vehicle can determine what stable state the vehicle will need to adjust to (for example, accelerating, decelerating, or stopping) based on the predicted behavior of the target.
- other factors may also be taken into consideration to determine the speed of the vehicle 200, such as the lateral position of the vehicle 200 on the traveling road, the curvature of the road, the proximity of static and dynamic targets, and so on.
- the computing device can also provide instructions to modify the steering angle of the vehicle 200 so that the self-driving car follows a given trajectory and/or maintains a target near the self-driving car (for example, , The safe horizontal and vertical distances of cars in adjacent lanes on the road.
- the above-mentioned vehicle 200 may be a car, truck, motorcycle, bus, boat, airplane, helicopter, lawn mower, recreational vehicle, playground vehicle, construction equipment, tram, golf cart, train, and trolley, etc.
- the application examples are not particularly limited.
- the radar system described in the embodiments of the present application can be applied to various fields.
- the radar systems in the embodiments of the present application include, but are not limited to, vehicle-mounted radars, roadside traffic radars, and others.
- Man-machine radar is another type of radar.
- an exemplary flow chart of the method for estimating the angle of arrival AOA in an embodiment of this application may include the following steps:
- Step 301 The signal receiving device inputs the echo signal to the processing device.
- Step 302 The processing device may use the echo signal and a preset first spatial grid to establish a first spatial spectrum.
- the preset step size of the first spatial grid here may be the first value.
- the first value here can represent a specific value or a range.
- the first value may be a value greater than the resolution of the radar system, for example, may be an integer multiple of the resolution. For example, if the resolution of the radar system is 2, then the step size of the first spatial grid may be 10. It should be understood that the first value may be determined according to an empirical value, and this application does not make a specific limitation.
- the processing device can arrange the input echo signals before establishing the first spatial spectrum.
- the sampling value in the signal period can be called the fast time corresponding to the distance
- the sampling between the signals is called the slow time corresponding speed
- the input echo signals are arranged in the form of a rectangular parallelepiped.
- the processing equipment can perform fast Fourier transform (FFT) along the fast time (fast time) and slow time (slow time) of the echo signal respectively, and then multiple range-Doppler maps (range-Doppler images) can be obtained.
- -doppler map, RDmap can be accumulated and combined into a final RDmap, as shown in Figure 5.
- the processing equipment can use the constant false-alram rate (CFAR) technology on the final RDmap to select a cluster of data composed of points with high signal-to-noise ratio, such as the points in the rectangle in Figure 5, using the first
- the spatial grid establishes the first spatial spectrum.
- the processing device may adopt a digital beamforming (digital beamforming, DBF) technology or a multiple signal classification (multiple signal classification, MUSIC) algorithm to establish the first spatial spectrum.
- DBF digital beamforming
- MUSIC multiple signal classification
- Step 303 The processing device performs target detection in the first spatial spectrum to obtain a spectrum peak in the first spatial spectrum.
- the processing device can perform target detection in the first spatial spectrum, and obtain two spectral peaks ⁇ 1 and ⁇ 2 as shown in FIG. 6.
- Step 304 The processing device calculates a first dispersion error of the spectral peak in the first spatial grid according to the first spatial grid and the detected spectral peaks.
- ⁇ 1 corresponds to the point ⁇ k in the grid
- ⁇ 2 corresponds to the point ⁇ m in the grid.
- ⁇ 1 with respect to the peak having discrete error ⁇ k ⁇ k
- ⁇ k ⁇ 1 - ⁇ k
- ⁇ 2 with respect to the discretization error ⁇ k + 1 ⁇ k
- ⁇ k ⁇ 2 - ⁇ k+1 .
- the processing equipment can use the signal data to estimate the error between ⁇ k and ⁇ 1 , and compensate the error to ⁇ k to obtain a new discrete point
- the corresponding is also an accurate estimation of the arrival angle.
- it can also be calculated
- the position of the m-th element can be represented by d m , if there are K echo signals illuminating the line array, then the k-th echo signal
- the steering vector of can be expressed as follows:
- ⁇ is the wavelength of the echo signal.
- the processing device can use the Taylor series to expand the steering vector of the echo signal near the point in the first spatial grid to obtain the following formula:
- Equation (3) E n represents the noise subspace of the echo signal, E n ⁇ C M * (Mk ), it should be understood, C denotes the set of complex numbers, i.e. E n belongs to M * (Mk) of the set, ⁇ is the step size of the first spatial grid.
- a commonly used assumption in array signal processing is that the echo signals are not correlated with each other, that is, the echo signals and noise are not correlated with each other:
- AR s A H represents the signal subspace, Represents the noise subspace, and they are all unknown, which can be obtained by eigenvalue decomposition of the matrix R through formula (6) and formula (7), that is, the features corresponding to the largest K eigenvalues of R are connected to form the signal subspace E s ⁇ C M * K, MK remaining smallest eigenvalues corresponding to eigenvectors constitute noise subspace E n ⁇ C M * (MK) .
- the processing device can calculate the points corresponding to the spectral peaks in the first spatial grid one by one according to formula (1)-formula (9) to obtain the first dispersion error of each spectral peak.
- ⁇ 1 and ⁇ 2 respectively spectral peaks in the first spatial spectrum.
- ⁇ 1 corresponds to the point ⁇ 1 in the first spatial grid, but because there is another spectral peak ⁇ 2 between ⁇ 1 and ⁇ 1 , it is necessary to calculate between ⁇ 1 and ⁇ 2 and split Out of the point ⁇ .
- splitting points in the first spatial grid may be performed before calculating the first discrete error, or may be performed after calculating the first discrete error. If it is performed after calculating the first discrete error, the processing device may recalculate the newly split points to obtain the first discrete error of these newly split points, and correct the newly split points in the first spatial grid.
- Step 305 The processing device corrects the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain the estimated value of the arrival angle of the echo signal.
- the processing device calculates the first dispersion error according to the above formula (1)-formula (9), it can correct the point corresponding to the spectral peak in the first spatial grid to obtain the estimated value of the arrival angle of the echo signal .
- the processing device calculates the first dispersion error according to the above formula (1)-formula (9)
- it can correct the point corresponding to the spectral peak in the first spatial grid to obtain the estimated value of the arrival angle of the echo signal . 6
- discretization error calculated [theta] 1 of the first formula and in accordance with the first discrete error ⁇ k [theta] 1 will be modified to Similarly, the point ⁇ m corresponding to ⁇ 2 can be corrected to therefore, It can be the estimated value of the arrival angle of the echo signal corresponding to ⁇ 1, It can be the estimated value of the arrival angle of the echo signal corresponding to ⁇ 2.
- the first spatial grid may also be modified through a loop operation.
- the following loop operations S1-S3 may be executed to modify the points corresponding to the spectral peaks in the first spatial grid.
- ⁇ 1 corresponds to the point ⁇ k in the first spatial grid represented by (1) in FIG. 8
- ⁇ 2 corresponds to the point ⁇ p .
- the processing device may calculate the first dispersion error of ⁇ k relative to ⁇ 1 and the first dispersion error of ⁇ p relative to ⁇ 2 according to the above formula (1)-formula (9).
- the first spatial grid can be corrected according to the calculated first discrete error to obtain the second spatial grid as shown in (2) in FIG. 8.
- ⁇ 1 corresponds to the point ⁇ k ′
- ⁇ 2 corresponds to ⁇ p ′.
- S2 Calculate the second dispersion error of the spectral peak in the second spatial grid according to the second spatial grid and the spectral peak.
- the processing equipment can determine that there are two spectral peaks between ⁇ p ′ and ⁇ p+1 , and therefore can split the point ⁇ q between ⁇ p ′ and ⁇ p+1 .
- the processing device can respectively calculate the dispersion error of ⁇ k ′ relative to ⁇ 1 , the dispersion error of ⁇ p ′ relative to ⁇ 2 , and the dispersion error of ⁇ q relative to ⁇ 3 through the above formula (1) to formula (9).
- the processing device can correct the second spatial grid according to the calculated discrete error of ⁇ k ′, the discrete error of ⁇ p ′, and the discrete error of ⁇ q to obtain a new one as shown in (3) in Fig. 8 The second spatial grid.
- the processing device can repeat the above S1-S3 operations to correct the new second spatial grid shown in (3) in FIG. 8 to obtain a more accurate estimate of the arrival angle.
- the stop condition of the loop operation can be as follows:
- Condition 1 The number of iterations is less than or equal to the first threshold.
- the initial number of iterations may be 0, and the processing device adds 1 to the number of iterations before calculating the discrete error based on the spatial grid and spectral peaks, and determines whether the number of iterations reaches the first threshold.
- the processing device uses the echo signal and the first spatial grid to establish a first spatial spectrum, and performs target detection in the first spatial spectrum, so that the spectral peak processing device can obtain the spectral peak and the first spatial grid according to the spectral peak and the first spatial grid, Calculate the first dispersion error of the spectral peak in the first spatial grid. And the points corresponding to the spectral peaks in the first spatial grid can be corrected according to the first discrete error to obtain the second spatial grid.
- the processing device may add 1 to the initial iteration number 0 to obtain the iteration number 1, and confirm that the iteration number 1 is less than the first threshold 2.
- the processing device can calculate the second dispersion error of the spectral peak in the second spatial grid based on the spectral peak and the second spatial grid.
- the processing device may also correct the points corresponding to the spectral peaks in the second spatial grid according to the second discrete error to obtain a new second spatial grid.
- the processing device may also add 1 to the number of iterations, and determine that the number of iterations is equal to the first threshold 2.
- the processing device may calculate the second discrete error of the spectral peak in the second spatial grid according to the new second spatial grid and the spectral peak. And according to the second discrete error, the points corresponding to the spectral peaks in the second spatial grid can be corrected to obtain a new second spatial grid.
- the processing device can also add 1 to the number of iterations, and determine that the number of iterations is greater than the first threshold 3, so the loop operation can be stopped.
- the processing device may determine the estimated value of the arrival angle according to the second spatial grid obtained from the last cycle operation.
- the initial number of iterations may be 1. After calculating the discrete error based on the spatial grid and spectral peaks, the processing device adds 1 to the number of iterations, and determines whether the number of iterations reaches the first threshold.
- the processing device uses the echo signal and the first spatial grid to establish a first spatial spectrum, and performs target detection in the first spatial spectrum to obtain a spectrum peak.
- the processing device may calculate the first dispersion error of the spectral peak in the first spatial grid according to the spectral peak and the first spatial grid.
- the processing device may correct the points corresponding to the spectral peaks in the first spatial grid according to the first discrete error to obtain the second spatial grid.
- the processing device can calculate the second discrete error of the spectral peak in the second spatial grid according to the spectral peak and the second spatial grid, and can also calculate the corresponding point of the spectral peak in the second spatial grid according to the second discrete error Make corrections to get a new second spatial grid.
- the processing device can also add 1 to the number of iterations 1 and determine that the number of iterations 2 is equal to the first threshold 2. Therefore, the processing device can calculate the spectral peaks in the second spatial grid based on the new second spatial grid and spectral peaks. The second discrete error in the grid. And according to the second discrete error, the points corresponding to the spectral peaks in the second spatial grid can be corrected to obtain a new second spatial grid.
- the processing device may also add 1 to the number of iterations 1, and determine that the number of iterations 3 is greater than the first threshold 2, and end the loop operation.
- the processing device may determine the estimated value of the arrival angle according to the second spatial grid obtained from the last cycle operation.
- the processing device uses the echo signal and the first spatial grid to establish a first spatial spectrum, and performs target detection in the first spatial spectrum to obtain a spectrum peak.
- the processing device may calculate the first dispersion error of the spectral peak in the first spatial grid according to the spectral peak and the first spatial grid.
- the processing device may correct the points corresponding to the spectral peaks in the first spatial grid according to the first discrete error to obtain the second spatial grid.
- the processing device may calculate the second discrete error A1 of the spectral peak in the second spatial grid according to the spectral peak and the second spatial grid, and correct the second spatial grid according to A1 to obtain a new second spatial grid.
- the processing device may also calculate a new second discrete error A2 according to the new second spatial grid and spectral peaks, and correct the second spatial grid according to A2 to obtain a new second spatial grid again. If
- the processing device may obtain the estimated value of the arrival angle of the echo signal according to the second spatial grid obtained in the last cycle operation.
- the above-mentioned S1-S3 cycle operation is optional, and the accuracy of the arrival angle can be set according to the radar system.
- the discrete error can be converged and stabilized. Therefore, by correcting the spatial grid according to the discrete error obtained by performing the loop operation, a more accurate estimate of the arrival angle can be obtained.
- the processing device can determine the estimated value of the arrival angle of the echo signal of the data within the rectangle as shown in FIG. 5. If the processing device also needs to calculate the estimated value of the arrival angle of other data in the RDmap shown in FIG. 5, the processing device can use the third spatial grid to establish the spatial spectrum.
- the third spatial grid may be obtained by the processing device correcting the first spatial grid according to the first discrete error, or may also be obtained by the processing device correcting the second spatial grid according to the second discrete error.
- the spatial spectrum of data other than the first cluster data in the RDmap is established through the third spatial grid, and the spectral peaks are more likely to overlap with the points in the third spatial grid, which can reduce the complexity of calculation.
- the processing device may also establish a spatial spectrum based on other data in the RDmap except the first cluster data and a preset first spatial grid to estimate the arrival angle of the other data.
- an exemplary flow chart of an AOA estimation method for the angle of arrival provided by this embodiment of the application may include the following steps:
- Step 1001 Input the echo signal.
- Step 1002 Establish a spatial spectrum based on the echo signal and the spatial grid.
- the spatial grid here may be the first spatial grid in the method embodiment shown in FIG. 3, or may also be the second spatial grid.
- Step 1003 Perform target detection in the spatial spectrum to obtain spectral peaks.
- Step 1004 Determine whether it is necessary to split the points of the spatial grid, if yes, execute step 1005, if otherwise, execute step 1006.
- Step 1005 Add a new point, and continue to perform step 1007.
- the dichotomy when adding new points, can be used to split the points in the spatial grid.
- Step 1006 According to the spatial grid and the detected spectral peaks, calculate the dispersion error of the points corresponding to the spectral peaks in the spatial grid.
- Step 1007 According to the calculated discrete error, correct the points corresponding to the spectral peaks in the spatial grid.
- Step 1008 whether the loop end condition is met, if yes, execute step 1009, if otherwise, return to execute step 1004.
- Step 1009 Obtain the estimated value of the arrival angle of the echo signal and the corrected space.
- the processing device 1100 can perform various steps of the processing device in the foregoing method, and in order to avoid repetition, the details are not described herein again.
- the processing device 1100 includes: a transceiver 1110, a processor 1120, and optionally, a memory 1130; the processor 1120 may be connected to the memory 1130 and the transceiver 1110 respectively, and the memory 1130 may also be connected to the transceiver 1110:
- the memory 1130 is used to store computer programs
- the transceiver 1110 is used to receive an input echo signal.
- the processor 1120 is configured to use the echo signal and a preset first spatial grid to establish a first spatial spectrum; and perform target detection in the first spatial spectrum to obtain Spectral peaks; and, according to the first spatial grid and the detected spectral peaks, calculate the first dispersion error of the spectral peaks in the first spatial grid; correct all the spectral peaks according to the first dispersion error
- the point corresponding to the spectral peak in the first spatial grid is used to obtain the estimated value of the arrival angle of the echo signal.
- the processor 1120 calculates the first discrete error of the spectral peak in the first spatial grid according to the first spatial grid and the detected spectral peaks
- the method for obtaining the first dispersion error of the spectral peak according to the expanded steering vector can refer to the relevant description of the method embodiment in FIG. 3 above.
- the processor 1120 corrects the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain the estimated value of the arrival angle of the echo signal Is specifically used for: correcting the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain a second spatial grid; according to the second spatial grid and the spectrum Peak, calculating the second dispersion error of the spectral peak in the second spatial grid; correcting the corresponding point of the spectral peak in the second spatial grid according to the second dispersion error to obtain the return The estimated value of the arrival angle of the wave signal.
- the processor 1120 is further configured to: when determining that the spectral peak splits into a new target point at the point corresponding to the first spatial grid, divide the spectral peak corresponding to the The point and the target point are used as spectral peaks in the first spatial spectrum.
- the processor 1120 uses the echo signal and a preset first spatial grid to establish the first spatial spectrum, it is specifically configured to: process the echo signal to obtain the range-Doppler Le figure RDmap; use the first cluster data in the RDmap and the first spatial grid to establish the first spatial spectrum.
- the processor 1120 is further configured to: correct the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain a third spatial grid;
- the data other than the first cluster data in the RDmap and the third spatial grid establish a second spatial spectrum, and the wave arrivals of the echo signals corresponding to the data other than the first cluster data are calculated.
- the estimated value of the angle is further configured to: correct the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain a third spatial grid;
- the data other than the first cluster data in the RDmap and the third spatial grid establish a second spatial spectrum, and the wave arrivals of the echo signals corresponding to the data other than the first cluster data are calculated.
- the estimated value of the angle is further configured to: correct the corresponding point of the spectral peak in the first spatial grid according to the first discrete error to obtain a third spatial grid;
- the data other than the first cluster data in the RDmap and the third spatial grid establish a second spatial spectrum
- the foregoing processing device may also be a chip, where the transceiver may be an input/output circuit or interface of the chip, and the processor may be a logic circuit, and the logic circuit may process the data to be processed according to the steps described in the foregoing method, and obtain the processed data.
- the data to be processed may be data received by the input circuit/interface, such as an input echo signal.
- the processed data may be data obtained according to the data to be processed, such as the estimated value of the angle of arrival.
- the processing device 1200 includes modules such as a modulation subsystem, a central processing subsystem, and a peripheral subsystem.
- the processing device in this embodiment can be used as a modulation subsystem therein.
- the modulation subsystem may include a processor 1203 and an interface 1204.
- the processor 1203 completes the function of the aforementioned processor 1120
- the interface 1204 completes the function of the aforementioned transceiver 1110.
- the modulation subsystem includes a memory 1206, a processor 1203, and a program stored in the memory 1206 and running on the processor.
- the processor 1203 executes the program, the processing device in the foregoing method embodiment is implemented. method.
- the memory 1206 can be non-volatile or volatile, and its location can be located inside the modulation subsystem or in the processing device 1200, as long as the memory 1206 can be connected to the The processor 1203 is fine.
- a computer-readable storage medium is provided, and an instruction is stored thereon.
- the instruction is executed, the method of the processing device in the foregoing method embodiment is executed.
- a computer program product containing instructions is provided, and when the instructions are executed, the method of the processing device in the foregoing method embodiment is executed.
- the processor mentioned in the embodiment of the present invention may be a central processing unit (Central Processing Unit, CPU), or may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSPs), and application-specific integrated circuits ( Application Specific Integrated Circuit (ASIC), Field Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc.
- the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
- the memory mentioned in the embodiment of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory.
- the non-volatile memory can be read-only memory (Read-Only Memory, ROM), programmable read-only memory (Programmable ROM, PROM), erasable programmable read-only memory (Erasable PROM, EPROM), and electrically available Erase programmable read-only memory (Electrically EPROM, EEPROM) or flash memory.
- the volatile memory may be a random access memory (Random Access Memory, RAM), which is used as an external cache.
- RAM static random access memory
- DRAM dynamic random access memory
- DRAM synchronous dynamic random access memory
- DDR SDRAM Double Data Rate Synchronous Dynamic Random Access Memory
- Enhanced SDRAM, ESDRAM Enhanced Synchronous Dynamic Random Access Memory
- Synchronous Link Dynamic Random Access Memory Synchronous Link Dynamic Random Access Memory
- DR RAM Direct Rambus RAM
- the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component
- the memory storage module
- the size of the sequence numbers of the above-mentioned processes does not mean the order of execution.
- the execution order of the processes should be determined by their functions and internal logic, and should not be used in the embodiments of the present invention.
- the implementation process constitutes any limitation.
- the disclosed system, device, and method can be implemented in other ways.
- the device embodiments described above are merely illustrative, for example, the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components can be combined or It can be integrated into another system, or some features can be ignored or not implemented.
- the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
- the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
- the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
- the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
- the technical solution of this application essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.
- the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code .
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Abstract
本申请提供一种波达角AOA估计方法和装置,涉及雷达通信技术领域,用以提高波达角估计值的准确性。该方法中,处理设备可以利用回波信号和预设的第一空间网格建立第一空间谱。并在第一空间谱中进行目标检测,得到第一空间中的谱峰。根据该第一空间网格和检测得到的谱峰,计算该谱峰在第一空间网格的第一离散误差。并可以根据该第一离散误差修正所述谱峰在第一空间网格中对应的点,得到所述回波信号的波达角的估计值。基于该方案,可以在计算空间谱中谱峰在空间网格中对应的点的离散误差,并根据离散误差修正空间网格中谱峰所对应的点,可以提高波达角估计值的准确性。
Description
本申请涉及雷达通信技术领域,尤其涉及一种波达角AOA估计方法和装置。
车载雷达是自动驾驶***中必不可少的传感器,通过车载雷达可以为车辆提供障碍物检测。车载雷达对信号处理提出了更高的要求,需要较低的计算复杂度以满足***实时性,需要足够高的精度以保证***的可靠性。波达角(angle of arrival,AOA)估计是雷达信号处理过程的重要部分。目前,AOA估计算法包含两大类:
首先是以旋转不变参数估计算法(estimation of signal parameters via rotational invariance technology,ESPRIT)和求根多重信号分类(root multiple fignal classification,root-MUSIC)为代表的能够计算出闭式解的算法。然而,这类算法由于阵列结构、估计精度等的限制,实际使用中较少。
其次是空间谱搜索类算法。空间谱搜索类算法首先需要计算空间谱,通过寻找空间谱谱峰来确定AOA估计值。由于空间角度是一个连续的变量,因此在计算空间谱时需要将连续的空间角度进行离散化处理,通过计算每个离散点上的幅值得到空间谱。然而,这类算法会有以下两个缺点:其一是空间谱的网格划分密集可能会导致计算的空间点数增多从而增加计算复杂度;其二是真实的空间角度不一定会落在划分的网格上,因此会存在量化误差导致较难获得最优的估计值。
发明内容
本申请提供一种波达角AOA估计方法和装置,用以减少波达角估计的计算量和提高波达角估计值的准确性。
第一方面,本申请提供一种波达角AOA估计方法,该方法可以由处理设备执行或者由类似于处理设备的其他设备执行。该方法中,处理设备可以利用回波信号和预设的第一空间网格建立第一空间谱。还可以在建立的该第一空间谱中进行目标检测,得到第一空间中的谱峰。根据该第一空间网格和检测得到的谱峰,计算该谱峰在第一空间网格的第一离散误差。处理设备可以根据该第一离散误差修正所述谱峰在第一空间网格中对应的点,得到所述回波信号的波达角的估计值。
基于该方案,可以在计算空间谱中谱峰在空间网格中对应的点的离散误差,并根据离散误差修正空间网格中谱峰所对应的点,可以提高波达角估计值的准确性。
在一种可能的实现方式中,所述第一空间网格的步长为第一值。这里的第一值可以是大于或等于雷达***的分辨率的整数倍的值。比如,步长可以是雷达***的分辨率的5倍、8倍等。应理解,该雷达***是发射所述回波信号对应的雷达信号的雷达***。例如,雷达***L发射了雷达信号,由阵列A反射形成回波信号,则该回波信号所对应的雷达信号即为雷达***L所发射的雷达信号。
基于该方案,在建立空间谱时,可以采用步长较大的空间网格,可以减少估计波达角时的计算量,并且结合计算得到的离散误差修正空间网格中谱峰对应的点,可以在减少计 算量的同时提高波达角估计值的准确性。
在一种可能的实现方式中,在根据所述第一空间网格和检测得到的所述谱峰,计算所述谱峰在所述第一空间网格的第一离散误差时,处理设备可以确定所述回波信号的导向矢量,可以将所述导向矢量在所述谱峰在所述第一空间网格中对应的点进行泰勒级数展开。处理设备可以根据展开后的所述导向矢量,得到所述谱峰的第一离散误差。
基于该方案,可以采用导向矢量在第一空间网格中对应的点进行泰勒级数展开,使得离散误差逼近一个收敛的值,可以较为容易的计算出离散误差。
在一种可能的实现方式中,该第一离散误差δ
k可以满足以下表达式:
基于该方案,可以根据上述公式计算得到谱峰在空间网格中对应的点的离散误差,以对空间网格进行修正,可以提高波达角估计值的准确性。
在一种可能的实现方式中,根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到所述回波信号的波达角的估计值时,可以根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第二空间网格。并根据所述第二空间网格和所述谱峰,计算所述谱峰在所述第二空间网格的第二离散误差。处理设备可以根据所述第二离散误差修正所述谱峰在所述第二空间网格中对应的点,得到所述回波信号的波达角的估计值。
另外需要说明的是,处理设备还可以循环执行上述操作,比如在计算得到第二离散误差之后,可以根据该第二离散误差再次修正第二空间网格中所述谱峰对应的点,得到新的第二空间网格,并可以根据新的第二空间网格和所述谱峰,计算得到新的第二离散误差。处理设备可以在满足迭代条件时,结束上述循环操作,并根据最后一次迭代得到的第二离散误差,修正所述谱峰在所述第二空间网格中对应的点,最终得到所述回波信号的波达角的估计值。
基于该方案,可以根据第二离散误差得到更加准确的波达角估计值,也可以根据上述循环操作多次将空间网格中谱峰所对应的点的离散误差,降低谱峰与真实的空间角度之间的误差,可以提高波达角估计值的准确性。
在一种可能的实现方式中,在所述第一空间谱中进行目标检测,得到所述第一空间谱中的谱峰之后,还可以在确定所述谱峰在所述第一空间网格所对应的点***出新的目标点时,将所述谱峰所对应的所述点和所述目标点作为所述第一空间谱中的谱峰。
基于该方案,谱峰所对应的空间网格的点之间有两个真实的空间角度时,可以将谱峰所对应的空间网格的点进行***,可以避免目标即真实的空间角度丢失。
在一种可能的实现方式中,利用回波信号和预设的第一空间网格建立第一空间谱时,可以对所述回波信号进行处理,得到距离-多普勒图(range-doppler map,RDmap)。处理设备还可以利用RDmap中的第一簇数据和第一空间网格建立第一空间谱。这里的第一簇数据可以是RDmap中的多簇数据中任意一簇数据,也可以是RDmap数据中信噪比较高的点组成的一簇数据。
基于该方案,可以对回波信号进行处理得到RDmap数据,可以在RDmap数据中选择信噪比较高的点,采用预设的第一空间网格建立第一空间谱。其中,采用信噪比较高的点建立空间谱,可以较为容易的检测得到谱峰。
在一种可能的实现方式中,处理设备还可以根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第三空间网格。并且还可以采用所述RDmap数据中除所述第一簇数据以外的其他数据和所述第三空间网格建立第二空间谱,计算所述除所述第一簇数据以外的其他数据所对应的回波信号的波达角的估计值。处理设备利用所述RDmap中的第一簇数据和所述第一空间网格建立所述第一空间谱。
基于该方案,在计算同一RDmap中的回波信号的波达角时,可以复用已经根据第一离散误差修正后的空间网格,可以进一步降低计算的复杂度。
第二方面,本申请实施例还提供一种波达角AOA估计装置,可以用来执行上述第一方面及第一方面的任意可能的实现方式中的操作。例如,波达角AOA估计装置可以包括用于执行上述第一方面或第一方面的任意可能的实现方式中的各个操作的模块或单元。比如包括通信单元和处理单元。
第三方面,本申请实施例还提供一种波达角AOA估计***,可以包括上述处理设备和雷达***。
第四方面,本申请实施例提供了一种芯片***,包括处理器,可选的还包括存储器;其中,存储器用于存储计算机程序,处理器用于从存储器中调用并运行计算机程序,使得安装有芯片***的通信装置执行上述第一方面或第一方面的任意可能的实现方式中的任一方法。
第五方面,本申请实施例提供了一种计算机程序产品,包括计算机程序代码,当计算机程序代码被通信设备的通信单元、处理单元或收发器、处理器运行时,使得通信设备可以执行上述第一方面或第一方面的任意可能的实现方式中的任一方法。
第六方面,本申请实施例提供了一种计算机可读存储介质,计算机可读存储介质存储有程序,程序使得通信设备执行上述第一方面或第一方面的任意可能的实现方式中的任一方法。
另外,上述第二方面至第五方面的有益效果请参考上述第一方面中对应的有益效果描述,这里不再重复赘述。
图1为本申请提供的一种雷达***示意图;
图2为本申请实施例提供的应用场景示意图;
图3为本申请实施例提供的一种波达角估计方法的示例性流程图之一;
图4为本申请实施例提供的回波信号排列方法示意图;
图5为本申请实施例提供的回波信号的RDmap示意图;
图6为本申请实施例提供的空间网格示意图之一;
图7为本申请实施例提供的空间网格示意图之一;
图8为本申请实施例提供的空间网格示意图之一;
图9为本申请实施例提供的循环次数与离散误差的关系示意图;
图10为本申请实施例提供的一种波达角估计方法的示例性流程图之一;
图11为本申请实施例提供的一种处理装置的示意图之一;
图12为本申请实施例提供的一种处理装置的示意图之一。
以下,对本申请实施例中的部分用语进行解释说明,以便于本领域技术人员理解。
1)、波达角(angle of arrival,AOA)估计,又称为角谱估计(angle spectral estimation,ASE)、波达方向(direction of arrival,DOA)估计。目的是估计出哪个发射机在工作以及发射机所处的方向,简单的说就是利用己方雷达接收来自目标发射机的来波方向进行估计。
2)、回波信号,是指信号经反射物反射后,被反射物吸收一部分能量,产生了具有衰减延迟的原信号,叠加上原信号行程。
3)、空间谱,指表示采样得到的信号在空间各个方向上的能量分布的图。
4)、导向矢量,是指示信号的方向的矢量,是阵列天线的所有阵元对具有能量的信源的响应。
需要说明的是,本申请实施例中,多个,是指两个或两个以上。另外,需要理解的是,在本申请的描述中,“第一”、“第二”等词汇,仅用于区分描述的目的,而不能理解为指示或暗示相对重要性,也不能理解为指示或暗示顺序。
为了使本申请实施例的目的、技术方案和优点更加清楚,下面将结合附图对本申请实施例作进一步地详细描述。
如图1所示,多输入多输出(multiple-input multipleoutput,MIMO)雷达***可以包括天线阵列101、单片微波集成电路(monolithic microwave integrated circuit,MMIC)102和处理单元103。天线阵列101可以包括多个发射天线和多个接收天线。
其中,单片微波集成电路102用于产生雷达信号,进而通过天线阵列101将雷达信号发出。雷达信号包括多个啁啾信号。雷达信号发出后,经一个或多个目标反射后形成回波信号,回波信号被接收天线接收。单片微波集成电路102还用于对天线阵列101接收到的回波信号进行变换和采样等处理,并将处理后的回波信号传输至处理单元103。单片微波集成电路102可以有一个或多个。
其中,处理单元103用于对回波信号进行快速傅里叶变换(Fast Fourier Transformation,FFT)、信号处理等操作,从而根据接收到的回波信号确定目标的距离、速度、方位角等信息。具体地,该处理单元103可以是微处理器(microcontroller unit,MCU)、中央处理器(central process unit,CPU)、数字信号处理器(digital signal processor,DSP)、现场可编程门阵列(field-programmable gate array,FPGA)、专用加速器等具有处理功能的器件。
此外,图1所示的雷达***还可以包括电子控制单元(electronic control unit,ECU)104,用于根据处理单元103处理后得到的目标距离、速度、方位角等信息对车辆进行控制,例如确定车辆的行使路线、控制车辆的速度等。
本申请实施例中的处理设备可以由上述处理单元103实现。
另外由于单个单片微波集成电路(射频芯片)102的通道规格数比较有限,***需要的收发通道数大于单个射频芯片时,需要多个射频芯片级联。因此,整个雷达***可能包括多个射频芯片级联,例如,发射天线阵列和接收天线阵列是多个MIMO级联得到的,通过接口连接模拟数字转换器(analog digital converter,ADC)通道输出的数据到处理单元 103,例如MCU,DSP,FPGA,通用处理单元(General Process Unit,GPU)等。又例如,MMIC和DSP可以集成在一个芯片中,称为片上***(System on chip,SOC)。又例如,MMIC和ADC,处理单元103可以集成在一个芯片中,构成SOC。另外,整车可能安装一个或多个雷达***,并且通过车载总线和中央处理器连接。中央处理器控制一个或多个车载传感器,包括一个或多个毫米波雷达传感器。
下面对本申请实施例的应用场景进行介绍。
图1所示的MIMO雷达***可以应用于具有自动驾驶功能的车辆。参见图2,为本申请实施例提供的具有自动驾驶功能的车辆200的功能框图。在一个实施例中,将车辆200配置为完全或部分地自动驾驶模式。例如,车辆200在处于自动驾驶模式时可以同时控制自身,并且可以通过人为操作来确定车辆及其周边环境的当前状态,确定周边环境中的至少一个其他车辆的可能行为,并确定该其他车辆执行可能行为的可能性相对应的置信水平,并基于所确定的信息来控制车辆200。在车辆200处于自动驾驶模式中时,可以将车辆200置为在没有和人交互的情况下操作。
车辆200可包括各种子***,例如行进***202、传感器***204、控制***206、一个或多个***设备208以及电源210、计算机***212和用户接口216。可选地,车辆200可包括更多或更少的子***,并且每个子***可包括多个元件。另外,车辆200的每个子***和元件可以通过有线或者无线互连。
行进***202可包括为车辆200提供动力运动的组件。在一个实施例中,行进***202可包括引擎218、能量源219、传动装置220和车轮/轮胎221。引擎218可以是内燃引擎、电动机、空气压缩引擎或其他类型的引擎组合,例如气油发动机和电动机组成的混动引擎,内燃引擎和空气压缩引擎组成的混动引擎。引擎218用于将能量源219转换成机械能量。
能量源219的示例包括汽油、柴油、其他基于石油的燃料、丙烷、其他基于压缩气体的燃料、乙醇、太阳能电池板、电池和其他电力来源。能量源219也可以为车辆200的其他***提供能量。
传动装置220可以将来自引擎218的机械动力传送到车轮221。传动装置220可包括变速箱、差速器和驱动轴。在一个实施例中,传动装置220还可以包括其他器件,比如离合器。其中,驱动轴可包括可耦合到一个或多个车轮221的一个或多个轴。
传感器***204可包括感测关于车辆200周边的环境的信息的若干个传感器。例如,传感器***204可包括定位***222(定位***可以是全球定位***(global positioning system,GPS)***,也可以是北斗***或者其他定位***)、惯性测量单元(inertial measurement unit,IMU)224、雷达226、激光测距仪228以及相机230。传感器***204还可包括被监视车辆200的内部***的传感器(例如,车内空气质量监测器、燃油量表、机油温度表等)。来自这些传感器中的一个或多个的传感器数据可用于检测对象及其相应特性(位置、形状、方向、速度等)。这种检测和识别是车辆200的安全操作的关键功能。
定位***222可用于估计车辆200的地理位置。IMU 224用于基于惯性加速度来感测车辆200的位置和朝向变化。在一个实施例中,IMU 224可以是加速度计和陀螺仪的组合。
雷达226可利用无线电信号来感测车辆200的周边环境内的目标。在一些实施例中,除了感测目标以外,雷达226还可用于感测目标的速度和/或前进方向。在一个具体示例中,雷达226可以采用图1所示的MIMO雷达***实现。
激光测距仪228可利用激光来感测车辆100所位于的环境中的目标。在一些实施例中, 激光测距仪228可包括一个或多个激光源、激光扫描器以及一个或多个检测器,以及其他***组件。
相机230可用于捕捉车辆200的周边环境的多个图像。相机230可以是静态相机或视频相机。
控制***206为控制车辆200及其组件的操作。控制***206可包括各种元件,其中包括转向***232、油门234、制动单元236、传感器融合算法238、计算机视觉***240、路线控制***242以及障碍物避免***244。
转向***232可操作来调整车辆200的前进方向。例如在一个实施例中可以为方向盘***。
油门234用于控制引擎218的操作速度并进而控制车辆200的速度。
制动单元236用于控制车辆200减速。制动单元236可使用摩擦力来减慢车轮221。在其他实施例中,制动单元236可将车轮221的动能转换为电流。制动单元236也可采取其他形式来减慢车轮221转速从而控制车辆200的速度。
计算机视觉***240可以操作来处理和分析由相机230捕捉的图像以便识别车辆200周边环境中的目标和/或特征。所述目标和/或特征可包括交通信号、道路边界和障碍物。计算机视觉***240可使用目标识别算法、运动中恢复结构(structure from motion,SFM)算法、视频跟踪和其他计算机视觉技术。在一些实施例中,计算机视觉***240可以用于为环境绘制地图、跟踪目标、估计目标的速度等等。
路线控制***242用于确定车辆200的行驶路线。在一些实施例中,路线控制***142可结合来自传感器238、GPS 222和一个或多个预定地图的数据以为车辆200确定行驶路线。
障碍物避免***244用于识别、评估和避免或者以其他方式越过车辆200的环境中的潜在障碍物。
当然,在一个实例中,控制***206可以增加或替换地包括除了所示出和描述的那些以外的组件。或者也可以减少一部分上述示出的组件。
车辆200通过***设备208与外部传感器、其他车辆、其他计算机***或用户之间进行交互。***设备208可包括无线通信***246、车载电脑248、麦克风250和/或扬声器252。
在一些实施例中,***设备208提供车辆200的用户与用户接口216交互的手段。例如,车载电脑248可向车辆200的用户提供信息。用户接口216还可操作车载电脑248来接收用户的输入。车载电脑248可以通过触摸屏进行操作。在其他情况中,***设备208可提供用于车辆200与位于车内的其它设备通信的手段。例如,麦克风250可从车辆200的用户接收音频(例如,语音命令或其他音频输入)。类似地,扬声器252可向车辆200的用户输出音频。
无线通信***246可以直接地或者经由通信网络来与一个或多个设备无线通信。例如,无线通信***246可使用3G蜂窝通信,例如码分多址(code division multiple access,CDMA)、EVD0、全球移动通信***(global system for mobile communications,GSM)/通用分组无线服务技术(general packet radio service,GPRS),或者4G蜂窝通信,例如长期演进(long term evolution,LTE),或者5G蜂窝通信。无线通信***246可利用WiFi与无线局域网(wireless local area network,WLAN)通信。在一些实施例中,无线通信***246可利用 红外链路、蓝牙或ZigBee与设备直接通信。其他无线协议,例如各种车辆通信***,例如,无线通信***246可包括一个或多个专用短程通信(dedicated short range communications,DSRC)设备,这些设备可包括车辆和/或路边台站之间的公共和/或私有数据通信。
电源210可向车辆200的各种组件提供电力。在一个实施例中,电源210可以为可再充电锂离子或铅酸电池。这种电池的一个或多个电池组可被配置为电源为车辆200的各种组件提供电力。在一些实施例中,电源210和能量源219可一起实现,例如一些全电动车中那样。
车辆200的部分或所有功能受计算机***212控制。计算机***212可包括至少一个处理器223,处理器223执行存储在例如存储器224这样的非暂态计算机可读介质中的指令225。计算机***212还可以是采用分布式方式控制车辆200的个体组件或子***的多个计算设备。
处理器223可以是任何常规的处理器,诸如商业可获得的中央处理器(central processing unit,CPU)。替选地,该处理器可以是诸如专用集成电路(application specific integrated circuits,ASIC)或其它基于硬件的处理器的专用设备。尽管图2功能性地图示了处理器、存储器、和在相同块中的计算机210的其它元件,但是本领域的普通技术人员应该理解该处理器、计算机、或存储器实际上可以包括可以或者可以不存储在相同的物理外壳内的多个处理器、计算机、或存储器。例如,存储器可以是硬盘驱动器或位于不同于计算机210的外壳内的其它存储介质。因此,对处理器或计算机的引用将被理解为包括对可以或者可以不并行操作的处理器或计算机或存储器的集合的引用。不同于使用单一的处理器来执行此处所描述的步骤,诸如转向组件和减速组件的一些组件每个都可以具有其自己的处理器,所述处理器只执行与特定于组件的功能相关的计算。
在此处所描述的各个方面中,处理器可以位于远离该车辆并且与该车辆进行无线通信。在其它方面中,此处所描述的过程中的一些在布置于车辆内的处理器上执行而其它则由远程处理器执行,包括采取执行单一操纵的必要步骤。
在一些实施例中,存储器224可包含指令225(例如,程序逻辑),指令225可被处理器223执行来执行车辆200的各种功能,包括以上描述的那些功能。存储器214也可包含额外的指令,包括向行进***202、传感器***204、控制***206和***设备208中的一个或多个发送数据、从其接收数据、与其交互和/或对其进行控制的指令。
除了指令225以外,存储器224还可存储数据,例如道路地图、路线信息,车辆的位置、方向、速度以及其它这样的车辆数据,以及其他信息。这种信息可在车辆200在自主、半自主和/或手动模式中操作期间被车辆200和计算机***212使用。
用户接口216,用于向车辆200的用户提供信息或从其接收信息。可选地,用户接口216可包括在***设备208的集合内的一个或多个输入/输出设备,例如无线通信***246、车载电脑248、麦克风250和扬声器252。
计算机***212可基于从各种子***(例如,行进***202、传感器***204和控制***206)以及从用户接口216接收的输入来控制车辆200的功能。例如,计算机***212可利用来自控制***206的输入以便控制转向单元232来避免由传感器***204和障碍物避免***244检测到的障碍物。在一些实施例中,计算机***212可操作来对车辆200及其子***的许多方面提供控制。
可选地,上述这些组件中的一个或多个可与车辆200分开安装或关联。例如,存储器 224可以部分或完全地与车辆200分开存在。上述组件可以按有线和/或无线方式来通信地耦合在一起。
可选地,上述组件只是一个示例,实际应用中,上述各个模块中的组件有可能根据实际需要增添或者删除,图2不应理解为对本申请实施例的限制。
在道路行进的自动驾驶汽车,如上面的车辆200,可以识别其周围环境内的目标以确定对当前速度的调整。所述目标可以是其它车辆、交通控制设备、或者其它类型的目标。在一些示例中,可以独立地考虑每个识别的目标,并且基于目标的各自的特性,诸如它的当前速度、加速度、与车辆的间距等,可以用来确定自动驾驶汽车所要调整的速度。
可选地,自动驾驶汽车车辆200或者与自动驾驶车辆200相关联的计算设备(如图2的计算机***212、计算机视觉***240、存储器224)可以基于所识别的目标的特性和周围环境的状态(例如,交通、雨、道路上的冰、等等)来预测所述识别的目标的行为。可选地,每一个所识别的目标都依赖于彼此的行为,因此还可以将所识别的所有目标全部一起考虑来预测单个识别的目标的行为。车辆200能够基于预测的所述识别的目标的行为来调整它的速度。换句话说,自动驾驶汽车能够基于所预测的目标的行为来确定车辆将需要调整到(例如,加速、减速、或者停止)什么稳定状态。在这个过程中,也可以考虑其它因素来确定车辆200的速度,诸如,车辆200在行驶的道路中的横向位置、道路的曲率、静态和动态目标的接近度等等。
除了提供调整自动驾驶汽车的速度的指令之外,计算设备还可以提供修改车辆200的转向角的指令,以使得自动驾驶汽车遵循给定的轨迹和/或维持与自动驾驶汽车附近的目标(例如,道路上的相邻车道中的轿车)的安全横向和纵向距离。
上述车辆200可以为轿车、卡车、摩托车、公共汽车、船、飞机、直升飞机、割草机、娱乐车、游乐场车辆、施工设备、电车、高尔夫球车、火车、和手推车等,本申请实施例不做特别的限定。
此外,同样需要说明的是,本申请实施例中所述的雷达***可以应用于多种领域,示例性地,本申请实施例中的雷达***包括但不限于车载雷达、路边交通雷达,无人机雷达。
基于上述图1和图2所示的应用场景,本申请提供一种波达角AOA估计方法,该方法可以应用于上述图1和图2所示的场景中,汽车自动驾驶中对波达角AOA的估计处理。如图3所示,为本申请实施例中波达角AOA估计方法的示例性流程图,可以包括以下步骤:
步骤301:信号接收设备将回波信号输入给处理设备。
步骤302:处理设备可以利用回波信号和预设的第一空间网格建立第一空间谱。
这里的预设的第一空间网格的步长可以是第一值。其中,这里的第一值可以表示一个具体的值,也可以是一个范围。该第一值可以是大于雷达***的分辨率的值,例如可以是分辨率的整数倍。举例来说,如果雷达***的分辨率为2,那么第一空间网格的步长可以是10。应理解,该第一值可以根据经验值确定,本申请不做具体限定。
处理设备在建立第一空间谱之前,可以对输入的回波信号进行排列。如图4所示,可以将信号周期内的采样值叫做快时间对应于距离,信号之间的采样成叫做慢时间对应速度,并将输入的回波信号排列成长方体形式。处理设备可以将回波信号分别沿着快时间(fast time)和慢时间(slow time)做快速傅里叶变换(fast fourier transform,FFT),就可以得到多个距离-多普勒图(range-doppler map,RDmap)。可以将这些RDmap进行累积处理,融 合为一张最终的RDmap,如图5所示。处理设备可以在最终的RDmap上采用恒虚警率(constant false-alram rate,CFAR)技术,选择信噪比较高的点组成的一簇数据,如图5中矩形内的点,采用第一空间网格建立第一空间谱。
其中,处理设备可以采用数字波束形成(digital beam forming,DBF)技术或者多重信号分类(multiple signal classification,MUSIC)算法建立第一空间谱。
步骤303:处理设备在所述第一空间谱中进行目标检测,得到所述第一空间谱中的谱峰。
处理设备可以在第一空间谱中进行目标检测,得到如图6中所示的θ
1和θ
2两个谱峰。
步骤304:处理设备根据所述第一空间网格和检测得到的所述谱峰,计算所述谱峰在所述第一空间网格的第一离散误差。
如图6所示,假设第一空间谱中有两个谱峰θ
1和θ
2,其中θ
1对应于网格中的点φ
k,θ
2对应于网格中的点φ
m。从图6中可以看出谱峰θ
1相对于φ
k具有离散误差δ
k,δ
k=θ
1-φ
k,θ
2相对于φ
k+1离散误差δ
k,δ
k=θ
2-φ
k+1。处理设备可以利用信号数据估计φ
k与θ
1之间的误差,并将误差补偿到φ
k上得到新的离散点
对应的也是精确的波达角估计值。同样的,也可以计算得到
以下,介绍本申请实施例中提供的第一离散误差δ
k的计算方法。
假设一个由M个阵元组成的线阵,M是大于0的整数,第m个阵元位置可以由d
m表示,如果有K个回波信号照射在线阵上,则第k个回波信号的导向矢量可以表示如下:
其中,μ
k=(2π/λ)sinθ
k,j
2=-1,λ是回波信号的波长。
处理设备可以利用泰勒级数,将回波信号的导向矢量在第一空间网格中的点附近进行展开,得到如下的公式:
简化上述公式(2)可以得到如下所示的公式:
公式(3)中的E
n表示回波信号的噪声子空间,E
n∈C
M*(M-k),应理解,C表示复数的集合,也就是说E
n属于M*(M-k)的集合,τ是第一空间网格的步长。具体来说,阵列信号处理中一个常用的假设是各个回波信号之间互不相关,即回波信号与噪声之间互不相关:
其中,s(t)=[s
1(t),…,s
k(t)]
T表示回波信号波形,i,z∈[1,2,…K]。
其中,s(t)=[s
1(t),…,s
k(t)]
T表示回波信号波形,i∈[1,2,…K],z∈[1,2,…M]。
利用上述公式(4)和公式(5)可以计算得到回波信号的协方差矩阵,记做:
公式(6)中AR
sA
H表示信号子空间,
表示噪声子空间,且都是未知的,可以通过公式(6)和公式(7)对矩阵R进行特征值分解获得,也就是R最大的K个特征值对应的特征相连组成了信号子空间E
s∈C
M*K,剩余的M-K个最小的特征值对应的特征向量组成了噪声子空间E
n∈C
M*(M-K)。
将公式(2)带入公式(3)中,展开并简化后,可以得到如下优化公式:
在公式(7)中,c
2,k与c
1,k的表达式如下所示:
通过上述表达式,求解公式(7)既可以得到δ
k的表达式:
处理设备可以根据公式(1)-公式(9)逐个对第一空间网格中谱峰所对应的点进行计算,得到每一个谱峰的第一离散误差。
在本申请实施例中,第一空间网格中的连续的两个点之间,可能存在不止一个谱峰。如图7所示,通过目标检测,检测到第一空间谱中存在两个谱峰,分别是θ
1和θ
2。其中,在第一空间网格中θ
1对应于点φ
1,但是由于在φ
1和φ
1之间还存在另一个谱峰θ
2,因此需要在φ
1和φ
2之间进行计算,***出点φ。
以下介绍如何在第一空间网格中对点进行***的方法:
如图7中的(1)所示是第一空间网格,针对每一个点(如φ
1、φ
2、φ
3)将连续的两个点之间进行二分,二分后得到的点可以记为φ。如果P(φ)>P(φ
1)+P(φ
2),则可以认为φ
1和φ
2之间存在谱峰,需要在φ
1和φ
2之间***出点φ。其中,P(φ)是φ在第一空间谱中的值,同理P(φ
1)是φ
1在第一空间谱中的值,P(φ
2)是φ
2在第一空间谱中的值。如图7中的(2)所示,在φ
1和φ
2中间***出新的点φ。
另外需要说明的是,上述在第一空间网格中对点进行***的操作可以在计算第一离散误差之前进行,也可以在计算第一离散误差之后进行。如果在计算第一离散误差之后进行,处理设备可以对新***出的点再次计算,得到这些新***出的点的第一离散误差,并在第一空间网格中修正新***出的点。
步骤305:处理设备根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到所述回波信号的波达角的估计值。
处理设备在根据上述公式(1)-公式(9)计算得到第一离散误差后,可以对第一空间网格中谱峰所对应的点进行修正,得到回波信号的波达角的估计值。如图6所示,可以根 据上述公式(1)-公式(9)计算得到θ
1的第一离散误差,并根据θ
1的第一离散误差将φ
k修正为
同样的,可以将θ
2所对应的点φ
m修正为
因此,
可以是θ
1所对应的回波信号的波达角的估计值,
可以是θ
2所对应的回波信号的波达角的估计值。
本申请实施例中还可以通过循环操作,对第一空间网格进行修正,比如可以通过如下的循环执行操作S1-S3,修正第一空间网格中谱峰所对应的点。
S1:根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第二空间网格。
如图8所示中的(1)所示,第一空间网格中存在θ
1、θ
2和θ
3三个谱峰。其中,θ
1对应于图8中的(1)表示的第一空间网格中的点φ
k,θ
2对应于点φ
p。处理设备可以根据上述公式(1)-公式(9)计算φ
k相对于θ
1的第一离散误差,以及计算φ
p相对于θ
2的第一离散误差。并且可以根据计算得到的第一离散误差,将第一空间网格进行修正,得到如图8中的(2)所示的第二空间网格。在第二空间网格中,θ
1对应于点φ
k′,θ
2对应于φ
p′。
S2:根据所述第二空间网格和所述谱峰,计算所述谱峰在所述第二空间网格的第二离散误差。
如图8中的(2)所示,在计算第二离散误差之前,可以针对每一个点计算是否需要***出新的点。其中,具体的方法可以参见如图7所示的方法实施例中的相关描述。处理设备可以确定在φ
p′和φ
p+1之间存在两个谱峰,因此可以在φ
p′和φ
p+1之间***出点φ
q。
处理设备可以通过上述公式(1)-公式(9)分别计算φ
k′相对于θ
1的离散误差,φ
p′相对于θ
2的离散误差,以及φ
q相对于θ
3的离散误差。
S3:根据所述第二离散误差修正所述谱峰在所述第二空间网格中对应的点,得到新的第二空间网格。
处理设备可以根据计算得到的φ
k′的离散误差,φ
p′的离散误差和φ
q的离散误差,对第二空间网格进行修正,得到如图8中的(3)所示的新的第二空间网格。
处理设备可以重复上述S1-S3的操作,对图8中的(3)所示的新的第二空间网格进行修正,得到较为准确的波达角的估计值。
其中,循环操作的停止条件可以如下所示:
条件1、迭代次数小于或等于第一阈值。
在一个示例中,初始迭代次数可以为0,处理设备在根据空间网格和谱峰,计算离散误差之前,将迭代次数进行加1处理,并判断迭代次数是否达到第一阈值。
举例来说,处理设备利用回波信号和第一空间网格建立第一空间谱,并在第一空间谱中进行目标检测,得到了谱峰处理设备可以根据谱峰和第一空间网格,计算谱峰在第一空间网格的第一离散误差。并且可以根据第一离散误差对谱峰在第一空间网格中所对应的点进行修正,得到第二空间网格。处理设备可以将初始迭代次数0进行加1处理,得到迭代次数1,并确认迭代次数1小于第一阈值2。因此,处理设备可以根据谱峰和第二空间网格,计算谱峰在第二空间网格的第二离散误差。处理设备还可以根据第二离散误差对谱峰在第二空间网格中所对应的点进行修正,得到新的第二空间网格。处理设备还可以将迭代次数进行加1处理,并确定迭代次数等于第一阈值2。处理设备可以根据新的第二空间网格和谱峰,计算谱峰在所述第二空间网格中的第二离散误差。并且可以根据第二离散误差,修正所述第二空间网格中谱峰所对应的点,得到新的第二空间网格。处理设备还可以将迭代次数进行加1处理,并确定迭代次数大于第一阈值3,因此可以停止循环操作。
处理设备可以根据最后一次循环操作得到的第二空间网格,确定波达角的估计值。
另一个示例中,初始迭代次数可以为1,处理设备在根据空间网格和谱峰,计算离散误差之后,将迭代次数进行加1处理,并判断迭代次数是否达到第一阈值。
举例来说,处理设备利用回波信号和第一空间网格建立第一空间谱,并在第一空间谱中进行目标检测,得到了谱峰。处理设备可以根据谱峰和第一空间网格,计算谱峰在第一空间网格的第一离散误差。处理设备可以根据第一离散误差对谱峰在第一空间网格中所对应的点进行修正,得到第二空间网格。处理设备可以根据谱峰和第二空间网格,计算谱峰在第二空间网格的第二离散误差,并且还可以根据第二离散误差对谱峰在第二空间网格中所对应的点进行修正,得到新的第二空间网格。处理设备还可以将迭代次数1进行加1处理,并确定迭代次数2等于第一阈值2,因此处理设备可以根据新的第二空间网格和谱峰,计算谱峰在所述第二空间网格中的第二离散误差。并且可以根据第二离散误差,修正所述第二空间网格中谱峰所对应的点,得到新的第二空间网格。处理设备还可以将迭代次数1进行加1处理,并确定迭代次数3大于第一阈值2,并结束循环操作。
处理设备可以根据最后一次循环操作得到的第二空间网格,确定波达角的估计值。
条件2、在执行第i次循环操作时得到的离散误差与执行第i-1次循环操作得到的离散误差之差,在指定范围内。
举例来说,处理设备利用回波信号和第一空间网格建立第一空间谱,并在第一空间谱中进行目标检测,得到了谱峰。处理设备可以根据谱峰和第一空间网格,计算谱峰在第一空间网格的第一离散误差。处理设备可以根据第一离散误差对谱峰在第一空间网格中所对应的点进行修正,得到第二空间网格。处理设备可以根据谱峰和第二空间网格,计算谱峰在第二空间网格的第二离散误差A1,并根据A1修正第二空间网格得到新的第二空间网格。处理设备还可以根据新的第二空间网格和谱峰,计算新的第二离散误差A2,并根据A2修正第二空间网格再次得到新的第二空间网格。如果|A2-A1|属于[a,b],那么处理设备可以结束循环操作。
处理设备可以根据最后一次循环操作得到的第二空间网格,得到回波信号的波达角的估计值。
另外需要说明的是,上述S1-S3的循环操作是可选的,可以根据雷达***对波达角的精度进行设置。如图9所示,通过执行循环操作,离散误差可以获得收敛和稳定,因此根据执行循环操作得到的离散误差修正空间网格,则可以得到一个较为准确的波达角的估计值。
通过上述操作,处理设备可以确定如图5中矩形内的数据的回波信号的波达角的估计值。如果处理设备还需要计算图5所示的RDmap中的其他数据的波达角的估计值,那么处理设备可以采用第三空间网格建立空间谱。
其中,第三空间网格可以是处理设备根据第一离散误差修正第一空间网格得到的,或者还可以是处理设备根据第二离散误差修正第二空间网格得到的。这样,通过第三空间网格建立RDmap中除第一簇数据以外的其他数据的空间谱,谱峰更容易与第三空间网格中的点重叠,可以减少计算的复杂度。
可选的,处理设备还可以根据RDmap中的除第一簇数据以外的其他数据和预设的第一空间网格建立空间谱,以估计所述其他数据的波达角。
以下根据具体的实施例对本申请提供的波达角AOA估计方法进行进一步的说明。如 图10所示,为本申请实施例提供的一种波达角AOA估计方法的示例性流程图,可以包括如下步骤:
步骤1001:输入回波信号。
步骤1002:根据回波信号和空间网格建立空间谱。
其中,这里的空间网格可以是上述图3所示的方法实施例中的第一空间网格,或者也可以是第二空间网格。
步骤1003:在空间谱中进行目标检测,得到谱峰。
步骤1004:判断是否需要对空间网格的点进行***,如果是则执行步骤1005,如果否则执行步骤1006。
这里的对空间网格的点进行***的方法可以参见上述图3所示的方法实施例中的相关描述,此处不再赘述。
步骤1005:增加新的点,继续执行步骤1007。
其中,在增加新的点时,可以使用二分法对空间网格中的点进行***。
步骤1006:根据空间网格和检测得到的谱峰,计算谱峰在空间网格中所对应的点的离散误差。
这里的计算离散误差的方法可以参见上述图3所示的方法实施例中的相关描述。
步骤1007:根据计算得到的离散误差,修正空间网格中谱峰所对应的点。
步骤1008:是否满足循环结束条件,如果是则执行步骤1009,如果否则返回执行步骤1004。
这里的循环结束条件可以参见上述条件1和条件2所示,此处不再赘述。
步骤1009:得到回波信号的波达角的估计值,以及修正后的空间。
基于与上述通信方法的同一构思,如图11所示,提供了一种处理装置1100。处理装置1100能够上述方法中由处理设备执行的各个步骤,为了避免重复,此处不再详述。处理装置1100包括:收发器1110、处理器1120,可选的,还包括,存储器1130;处理器1120可以分别与存储器1130和收发器1110相连,所述存储器1130也可以与收发器1110相连:
所述存储器1130,用于存储计算机程序;
示例的,所述收发器1110,用于接收输入的回波信号。所述处理器1120,用于利用回波信号和预设的第一空间网格建立第一空间谱;并,在所述第一空间谱中进行目标检测,得到所述第一空间谱中的谱峰;以及,根据所述第一空间网格和检测得到的所述谱峰,计算所述谱峰在所述第一空间网格的第一离散误差;根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到所述回波信号的波达角的估计值。
其中,所述谱峰在所述第一空间网格的第一离散误差计算方法可以参见如图3所示的方法实施例中的相关描述,重复之处不再赘述。
在一种设计中,所述处理器1120在根据所述第一空间网格和检测得到的所述谱峰,计算所述谱峰在所述第一空间网格的第一离散误差时,具体用于:确定所述回波信号的导向矢量;将所述导向矢量在所述谱峰在所述第一空间网格中对应的点进行泰勒级数展开;根据展开后的所述导向矢量,得到所述谱峰的第一离散误差。
其中,根据展开后的导向矢量,得到所述谱峰的第一离散误差的方法可以参见上述图3中方法实施例的相关描述。
在一种设计中,所述处理器1120在根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到所述回波信号的波达角的估计值时,具体用于:根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第二空间网格;根据所述第二空间网格和所述谱峰,计算所述谱峰在所述第二空间网格的第二离散误差;根据所述第二离散误差修正所述谱峰在所述第二空间网格中对应的点,得到所述回波信号的波达角的估计值。
在一种设计中,所述处理器1120还用于:确定所述谱峰在所述第一空间网格所对应的点***出新的目标点时,将所述谱峰所对应的所述点和所述目标点作为所述第一空间谱中的谱峰。
其中,在第一空间网格中***新的目标点的方法可以参见上述图3所示的方法实施例中的相关描述。
在一种设计中,所述处理器1120在利用回波信号和预设的第一空间网格建立第一空间谱时,具体用于:对所述回波信号进行处理,得到距离-多普勒图RDmap;利用所述RDmap中的第一簇数据和所述第一空间网格建立所述第一空间谱。
其中,对回波信号进行处理得到RDmap的方法可以参见上述图3中所示的方法实施例中的相关描述。
在一种设计中,所述处理器1120还用于:根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第三空间网格;采用所述RDmap中除所述第一簇数据以外的其他数据和所述第三空间网格建立第二空间谱,计算所述除所述第一簇数据以外的其他数据所对应的回波信号的波达角的估计值。
上述处理装置还可以为芯片,其中收发器可以为芯片的输入/输出电路或者接口,处理器可以为逻辑电路,逻辑电路可以根据上述方法方面所描述的步骤对待处理的数据进行处理,获取处理后的数据。待处理的数据可以是输入电路/接口接收的数据,比如输入的回波信号。处理后的数据可以是根据待处理的数据得到的数据,比如波达角的估计值。
图12示出本实施例的另一种形式。处理装置1200中包括调制子***、中央处理子***、周边子***等模块。本实施例中的处理设备可以作为其中的调制子***。具体的,该调制子***可以包括处理器1203,接口1204。其中处理器1203完成上述处理器1120的功能,接口1204完成上述收发器1110的功能。作为另一种变形,该调制子***包括存储器1206、处理器1203及存储在存储器1206上并可在处理器上运行的程序,该处理器1203执行该程序时实现上述方法实施例中处理设备的方法。需要注意的是,所述存储器1206可以是非易失性的,也可以是易失性的,其位置可以位于调制子***内部,也可以位于处理装置1200中,只要该存储器1206可以连接到所述处理器1203即可。
作为本实施例的另一种形式,提供一种计算机可读存储介质,其上存储有指令,该指令被执行时执行上述方法实施例中处理设备的方法。
作为本实施例的另一种形式,提供一种包含指令的计算机程序产品,该指令被执行时执行上述方法实施例中处理设备的方法。
应理解,本发明实施例中提及的处理器可以是中央处理单元(Central Processing Unit,CPU),还可以是其他通用处理器、数字信号处理器(Digital Signal Processor,DSP)、专用集成电路(Application Specific Integrated Circuit,ASIC)、现成可编程门阵列(Field Programmable Gate Array,FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、 分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
还应理解,本发明实施例中提及的存储器可以是易失性存储器或非易失性存储器,或可包括易失性和非易失性存储器两者。其中,非易失性存储器可以是只读存储器(Read-Only Memory,ROM)、可编程只读存储器(Programmable ROM,PROM)、可擦除可编程只读存储器(Erasable PROM,EPROM)、电可擦除可编程只读存储器(Electrically EPROM,EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory,RAM),其用作外部高速缓存。通过示例性但不是限制性说明,许多形式的RAM可用,例如静态随机存取存储器(Static RAM,SRAM)、动态随机存取存储器(Dynamic RAM,DRAM)、同步动态随机存取存储器(Synchronous DRAM,SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM,DDR SDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM,ESDRAM)、同步连接动态随机存取存储器(Synchlink DRAM,SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM,DR RAM)。
需要说明的是,当处理器为通用处理器、DSP、ASIC、FPGA或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件时,存储器(存储模块)集成在处理器中。
应注意,本文描述的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
应理解,在本申请的各种实施例中,上述各过程的序号的大小并不意味着执行顺序的先后,各过程的执行顺序应以其功能和内在逻辑确定,而不应对本发明实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到,结合本文中所公开的实施例描述的各示例的单元及算法步骤,能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行,取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到,为描述的方便和简洁,上述描述的***、装置和单元的具体工作过程,可以参考前述方法实施例中的对应过程,在此不再赘述。
在本申请所提供的几个实施例中,应该理解到,所揭露的***、装置和方法,可以通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如,所述单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个***,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口,装置或单元的间接耦合或通信连接,可以是电性,机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是或者也可以不是物理单元,即可以位于一个地方,或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储介质中。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(可以是个人计 算机,服务器,或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、只读存储器(Read-Only Memory,ROM)、随机存取存储器(Random Access Memory,RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述,仅为本申请的具体实施方式,但本申请的保护范围并不局限于此,任何熟悉本技术领域的技术人员在本申请揭露的技术范围内,可轻易想到变化或替换,都应涵盖在本申请的保护范围之内。因此,本申请的保护范围应所述以权利要求的保护范围为准。
Claims (12)
- 一种波达角AOA估计方法,其特征在于,包括:利用回波信号和预设的第一空间网格建立第一空间谱;在所述第一空间谱中进行目标检测,得到所述第一空间谱中的谱峰;根据所述第一空间网格和检测得到的所述谱峰,计算所述谱峰在所述第一空间网格的第一离散误差;根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到所述回波信号的波达角的估计值。
- 根据权利要求1所述的方法,其特征在于,所述根据所述第一空间网格和检测得到的所述谱峰,计算所述谱峰在所述第一空间网格的第一离散误差,包括:确定所述回波信号的导向矢量;将所述导向矢量在所述谱峰在所述第一空间网格中对应的点进行泰勒级数展开;根据展开后的所述导向矢量,得到所述谱峰的第一离散误差。
- 根据权利要求1-3任一所述的方法,其特征在于,所述根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到所述回波信号的波达角的估计值,包括:根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第二空间网格;根据所述第二空间网格和所述谱峰,计算所述谱峰在所述第二空间网格的第二离散误差;根据所述第二离散误差修正所述谱峰在所述第二空间网格中对应的点,得到所述回波信号的波达角的估计值。
- 根据权利要求1-4任一所述的方法,其特征在于,所述在所述第一空间谱中进行目标检测,得到所述第一空间谱中的谱峰之后,还包括:确定所述谱峰在所述第一空间网格所对应的点***出新的目标点时,将所述谱峰所对应的所述点和所述目标点作为所述第一空间谱中的谱峰。
- 根据权利要求1-5任一所述的方法,其特征在于,所述利用回波信号和预设的第一空间网格建立第一空间谱,包括:对所述回波信号进行处理,得到距离-多普勒图RDmap;利用所述RDmap中的第一簇数据和所述第一空间网格建立所述第一空间谱。
- 根据权利要求6所述的方法,其特征在于,还包括:根据所述第一离散误差修正所述谱峰在所述第一空间网格中对应的点,得到第三空间网格;采用所述RDmap中除所述第一簇数据以外的其他数据和所述第三空间网格建立第二空间谱,计算所述除所述第一簇数据以外的其他数据所对应的回波信号的波达角的估计值。
- 一种波达角AOA估计装置,其特征在于,包括:接收器,用于接收输入的回波信号;处理器,用于执行如所述权利要求1-7中任一项所述的方法。
- 一种波达角AOA估计装置,其特征在于,包括处理器和存储器;所述存储器,存储有计算机程序或指令;所述处理器,用于执行所述存储器中存储的计算机程序或指令,使得权利要求1-7中任一项所述的方法被执行。
- 一种计算机可读存储介质,其特征在于,存储有计算机可执行指令,所述计算机可执行指令用于使计算机执行如权利要求1-7中任一项所述的方法。
- 一种计算机程序产品,其特征在于,包含有计算机可执行指令,所述计算机可执行指令用于使计算机执行如权利要求1-7中任一项所述的方法。
- 一种芯片,其特征在于,所述芯片与存储器耦合,用于读取并执行所述存储器中存储的程序指令,以实现如权利要1-7中任一项所述的方法。
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