CN107121670B - Anti-unmanned aerial vehicle defense method based on synthetic aperture radar - Google Patents
Anti-unmanned aerial vehicle defense method based on synthetic aperture radar Download PDFInfo
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Abstract
The invention relates to a low-complexity high-precision defense method for a small unmanned aerial vehicle. First, a beat signal is obtained by mixing in the receiver front end. Secondly, distance direction FFT is carried out on the beat signals, and the antenna array is virtualized into a uniform linear array and beam forming is carried out by utilizing phase compensation so as to improve the signal to noise ratio. And estimating the altitude angle and the distance of the target after signal detection by using the improved CFAR algorithm of the unit average selection criterion. And finally, carrying out azimuth compression according to the obtained distance and the altitude angle to obtain the image of the unmanned aerial vehicle. For the low-altitude low-speed unmanned aerial vehicle, a position of the target can be obtained by the radar when the radar rotates for one circle, and then the motion trail of the target is drawn. The invention creatively combines SAR imaging and airspace signal processing algorithm, and can monitor the airspace with unknown height without interruption.
Description
Technical Field
The invention relates to the field of radar signal processing, in particular to a defense method for an anti-unmanned aerial vehicle based on a synthetic aperture radar.
Background
At present, the requirement of national large-scale infrastructure, national defense key facilities, civil houses, enterprise important facilities and the like on the anti-unmanned aerial vehicle system for peripheral low-altitude security defense is urgent and higher. Have characteristics such as flying height is on the low side, the volume is less to miniature unmanned aerial vehicle especially, be difficult for discovering during the invasion, also be difficult to counter-control the unmanned aerial vehicle of invasion, consequently have great potential safety hazard. In China, the 'black flying' event of the unmanned aerial vehicle is also frequently generated. 28 th and 29 th 12 th month in 2013, a company without aerial photography surveying and mapping qualification in Beijing is free from arranging personnel to operate an unmanned aerial vehicle to lift off for shooting under the condition of no application for airspace, so that a plurality of civil airliners are avoided and delayed. And in 29 months of 1 year 2015, the unmanned aerial vehicle breaks into the white house, and in 24 months of 4 years 2015, an unmanned aerial vehicle falls in the first phase mansion of japan. At present, anti-unmanned aerial vehicle defense methods in various countries can be divided into three main categories in principle: 1. the system comprises an interference blocking class 2, a direct destroying class 3, a monitoring control class, an AUDS system developed in the United kingdom as a representative, a Ku waveband electronic scanning air defense radar, a photoelectric indicator, a visible light/infrared camera, target tracking software and a directional radio frequency inhibition/interference system, and can detect, track, identify, interfere and stop the unmanned aerial vehicle within the range of 8 kilometers. The systems briefly described above are emphasized, and certain guarantees are provided on the effectiveness and accuracy of interception, but the systems are more suitable for the national military level, are huge, have complex control instructions and high cost, and cannot be used in a large scale. The system provided by the application is just directly attacking the pain point, and provides a defense method which is based on a low-complexity hardware platform, is easy to operate and ensures a certain degree of effectiveness.
Disclosure of Invention
In order to solve the existing problems, the invention provides a defense method for an anti-unmanned aerial vehicle based on a synthetic aperture radar, aiming at the problems of high manufacturing cost, large volume, manual operation and small defense range of the traditional defense method for the anti-unmanned aerial vehicle, the defense method for the unmanned aerial vehicle is designed to be small in volume, light in weight, simple in structure and low in loss, and in order to achieve the purpose, the defense method for the anti-unmanned aerial vehicle based on the synthetic aperture radar comprises the following steps:
the method comprises the following steps: the anti-unmanned aerial vehicle defense device based on the synthetic aperture radar is characterized in that a mechanical turntable carrying antenna of the anti-unmanned aerial vehicle defense device does uniform circular motion at an angular velocity omega, 24h uninterrupted monitoring of the whole airspace is realized by emitting multiple frequency signals through 360-degree circular scanning, and the antenna receives echo signals, performs beat signal processing and transmits the echo signals to a signal processing module for processing;
step two: taking the real part of the obtained difference frequency signal to perform Fast Fourier Transform (FFT) in the distance direction, and performing equivalent to distance direction compression;
step three: performing phase compensation and beam forming preprocessing on the data obtained in the step two, enabling the 4-transmission 8-reception antenna to be equivalent to a 1 x 32 virtual array, and simultaneously improving the signal-to-noise ratio;
step four: performing CFAR (constant false alarm rate) detection, namely constant false alarm rate detection, on the data obtained in the step three, screening signals to reduce data volume, then estimating the distance of the target, and estimating the altitude angle of the target by using a Capon method;
step five: and imaging and displaying the target through azimuth compression based on the information obtained in the step.
Further, the anti-unmanned aerial vehicle defense device based on the synthetic aperture radar comprises a signal transmitting and receiving module and a signal processing imaging module;
the signal transmitting and receiving module comprises a mechanical turntable, a 4-transmitting 8-receiving millimeter wave antenna and a signal transmitting and receiving chip, wherein the mechanical turntable carries the millimeter wave antenna to perform 360-degree annular scanning, the signal transmitting and receiving chip generates an excitation signal to control the antenna to transmit linear frequency modulation continuous waves and receive echo signals, and meanwhile, the signals subjected to difference frequency processing are sent to the signal processing module;
the signal processing module comprises distance direction compression, parameter estimation and SAR imaging, and the distance direction compression reduces the calculated amount of subsequent processing signals; obtaining information such as the distance and the altitude angle of the target through parameter estimation; and SAR imaging is carried out to obtain azimuth information of the target and a track of the target motion.
Further, the transmitting signal in the first step is a sawtooth wave of LFMCW, and the intermediate frequency signal is sampled to obtain echo data, wherein the intermediate frequency signal yi(t) is represented by the formula (1):
in formula (1), v is the radial velocity of the target relative to the radar, A is the amplitude of the transmitted signal, A0In order to receive the amplitude of the signal,
is the frequency modulation rate, B is the signal bandwidth, T is the signal emission period, r is the target distance, c is the speed of light, f0Is the carrier frequency, T is the time, T is the emission period of the first set of sawtooth signals, τdFor the target echo delay, i represents the ith transmit period.
Further, the transmission signal in the step one is a sawtooth wave of LFMCW, and a mathematical expression of the radar transmission signal is as follows:
in the formula A0To transmit signal amplitude, f0The carrier frequency for transmitting the sawtooth wave, mu is the slope of the sawtooth wave, T is the transmission period of the sawtooth wave, rect () is a window function;
from this, an expression for the corresponding echo signal can be written:
in the formula
R (t) is an expression in the formula x, and sigma is a constant related to the reflection coefficient of the target flying object;
the difference frequency signal of the LFMCW SAR is formed at the front end of the receiver, and after the difference frequency signal of one period is subjected to band-pass filtering, the difference frequency signal can be expressed as:
mu is the frequency modulation rate of the distance direction, and A is the difference frequency signal amplitude.
Further, the third step specifically includes the following steps:
3.1) carrying out phase compensation and beam forming on the intermediate frequency domain signals, virtualizing the array signals into a linear array after carrying out phase compensation, wherein the wave path difference between two adjacent antennas is d sin theta, in the array antenna which is transmitted by 4 and received by 8 under the actual condition, the wave path difference between a virtual receiving antenna 4n and a virtual receiving antenna 4n +1 is not equal to d sin theta, and phase compensation is required to be carried out to change the array into a uniform linear array;
and (3) performing phase compensation on the signals:
YVFFC＝T⊙YVFF(5)；
wherein the content of the first and second substances,
YVFFcomplex vector of frequency spectrum unit where target is located:
3.2) the array receiving signals are received by adopting a narrow beam formed by a windowing digital beam forming technology, so that clutter interference signals can be inhibited while array gain is obtained, and the target detection probability is improved;
suppose the beam center azimuth is θ0Considering the transmitting and receiving array structure of the system, the space domain steering vector is as follows:
can be obtained by pairing Nt×NrCarrying out weighted summation on the array element signals of the virtual receiving antenna, wherein the output signals of the conventional non-adaptive wave beams are as follows:
Z＝(w⊙as(θ0))HYVFFC(7)；
in the formula, H represents conjugate transpose, and the window function w is NtNr× 1, data weighting providing angular domain sidelobe suppression, steering vector as(θ0) Provide for the signal from theta0The maximum coherent accumulation of the direction signals carries out beam forming on all the distance-speed units to obtain
Further, the step 4 specifically includes the following steps:
4.1) carrying out constant false alarm detection on the target, and carrying out signal detection by adopting an improved CFAR algorithm of a unit average selection criterion; the CFAR detection calculation amount of all distance-speed units is large, whether the amplitude value of the distance unit is an area peak value or not is judged before CFAR detection, and useless signal processing can be avoided;
input cell signal is Zc＝Z⊙Z*The symbol denotes the conjugate of the vector, and Z iscComparing the value of each distance-speed unit with a threshold value, and if the value is greater than the threshold value, determining that a target exists at the point;
wherein the threshold product factor calculation formula is:
in the formula NcIs the number of units, pfaIs the false alarm probability;
4.2) carrying out Capon method angle measurement in the altitude angle dimension, and traversing the range to select the angle range in which the beam forming gain reaches the maximum value so as to reduce the calculated amount and obtain the estimated value angle _ E of the altitude angle. The data of the altitude angle dimension are weighted and summed, the weight is a guide vector written by the altitude angle estimation value, and then the shortest distance between the target and the radar is estimated by using the following formula
Wherein
As an estimate of the target-to-radar distance, fmaxThe frequency represented by the peak value of the signal after the beam forming and the CFAR detection;
will be provided with
Carry-in (4) to obtain approximate azimuthal frequency modulation
And after interpolation distance migration correction is carried out, azimuth compression is carried out to image the target.
Further, the specific steps of constant false alarm detection in step 4.1 are as follows:
1. number of protection units G c2, number of reference units Nc＝32；
2. According to formula zm＝z⊙z*Calculating the square of the amplitude module value of each point of the frequency spectrum;
3. detecting and calculating the j unit
Of the j-17 th to j-2 th units x1And the mean x of the j +2 th to j +17 th cells2If, if
The point is considered to be targeted. For edge data detection, if j < 17, then the mean is calculated over all reference cells.
The invention relates to an anti-unmanned aerial vehicle defense method based on a synthetic aperture radar, which designs two-transmitting four-receiving antennas working in a K wave band and carried on a rotatable circular table, realizes 360-degree omnibearing space scanning through mechanical rotary scanning, and has the characteristics of small volume, light weight, simple structure and low loss. The signal processing algorithm has four advantages as follows:
1) the wide-area circular track is circularly scanned, and a 360-degree radiation range can be formed by rotating one circle, so that a scanning area is enlarged;
2) the airspace parameter estimation is combined with the SAR classical RD algorithm, so that the problem that the traditional SAR can only detect a ground target is solved;
3) the signal processing is firstly mixed with the frequency of the original transmitting signal instead of the traditional frequency mixing with the carrier frequency, so that the calculation complexity and the calculation amount are greatly reduced;
4) the virtual array and the application of beam forming improve the performance of the whole system in a low signal-to-noise ratio environment.
Drawings
FIG. 1 is a flow chart of the algorithm of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention;
FIG. 3 is a schematic diagram of waveforms for emitting different sawtooth waveforms in accordance with the present invention;
FIG. 4 is a flow chart of a virtual array schematic algorithm of the present invention;
FIG. 5 is a graph of an echo signal prior to preprocessing in accordance with the present invention;
FIG. 6 is a graph of the fast time dimension FFT and beamforming of the present invention;
FIG. 7 is a diagram illustrating a CFAR detection simulation of the present invention;
FIG. 8 is a diagram illustrating a target coordinate estimation simulation of the present invention;
FIG. 9 is a schematic diagram of a CFAR according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the following detailed description and accompanying drawings:
the invention relates to a low-complexity high-precision defense method for a small unmanned aerial vehicle and a target detection and parameter calculation method. The system carries a millimeter wave antenna through a mechanical turntable to perform 360-degree circular track sweeping on an airspace with unknown height, and sends a linear frequency modulation sawtooth wave with fixed bandwidth as shown in figure 3. First, as shown in fig. 1, a beat signal is obtained by mixing in the receiver front end. Secondly, distance direction FFT is carried out on the beat signals, and the antenna array is virtualized into a uniform linear array and beam forming is carried out by utilizing phase compensation so as to improve the signal to noise ratio. And estimating the altitude angle and the distance of the target after signal detection by using the improved CFAR algorithm of the unit average selection criterion. And finally, carrying out azimuth compression according to the obtained distance and the altitude angle to obtain the image of the unmanned aerial vehicle. For the low-altitude low-speed unmanned aerial vehicle, a position of the target can be obtained by the radar when the radar rotates for one circle, and then the motion trail of the target is drawn. The invention creatively combines SAR imaging and airspace signal processing algorithm, and can monitor the airspace with unknown height without interruption.
In the specific implementation method, the radar adopts a four-transmitting eight-receiving antenna array, and the transmitting signals adopt transmitting signals as a group of carrier frequencies f0And in the transmission period T, the sawtooth wave signals with a certain sweep frequency bandwidth B are transmitted by the plurality of transmitting antennas in sequence. The system parameters are shown in the following table:
table 1: system simulation parameters
In the specific implementation method, the anti-unmanned aerial vehicle defense device based on the synthetic aperture radar comprises a signal transmitting and receiving module and a signal processing imaging module as shown in fig. 2;
the signal transmitting and receiving module comprises a mechanical turntable, a four-transmitting eight-receiving millimeter wave antenna and a signal transmitting and receiving chip, wherein the mechanical turntable carries the millimeter wave antenna to perform 360-degree annular scanning, the signal transmitting and receiving chip generates an excitation signal to control the antenna to transmit linear frequency modulation continuous waves and receive echo signals, and meanwhile, the signals subjected to difference frequency processing are transmitted to a signal processing module;
the signal processing module comprises distance direction compression, parameter estimation and SAR imaging, wherein the distance direction compression reduces the calculated amount of subsequent processing signals; obtaining information such as the distance and the altitude angle of the target through parameter estimation; and SAR imaging is carried out to obtain azimuth information of the target and a track of the target motion.
The specific embodiment discloses a defense method for an anti-unmanned aerial vehicle based on a synthetic aperture radar, which comprises the following steps as shown in fig. 1:
the method comprises the following steps: the anti-unmanned aerial vehicle defense device based on the synthetic aperture radar is characterized in that a mechanical turntable carrying antenna of the anti-unmanned aerial vehicle defense device does uniform circular motion at an angular velocity omega, 24h uninterrupted monitoring of the whole airspace is realized by emitting multiple frequency signals through 360-degree circular scanning, and the antenna receives echo signals, performs beat signal processing and transmits the echo signals to a signal processing module for processing;
step two: taking the real part of the obtained difference frequency signal to perform Fast Fourier Transform (FFT) in the distance direction, and performing equivalent to distance direction compression;
step three: and C, performing phase compensation and beam forming preprocessing on the data obtained in the step two, enabling the four-transmitting eight-receiving antenna to be equivalent to a 1 x 32 virtual array, and improving the signal-to-noise ratio.
Step four: performing CFAR (constant false alarm rate) detection, namely constant false alarm rate detection, on the data obtained in the step three, screening signals to reduce data volume, then estimating the distance of the target, and estimating the altitude angle of the target by using a Capon method;
step five: and imaging and displaying the target through azimuth compression based on the information obtained in the step.
Wherein the transmitting signal in the first step is as shown in fig. 3, and the intermediate frequency signal is sampled to obtain echo data, wherein the intermediate frequency signal yi(t) is represented by the formula (1):
in formula (1), v is the radial velocity of the target relative to the radar, A is the amplitude of the transmitted signal, A0In order to receive the amplitude of the signal,
is the frequency modulation rate, B is the signal bandwidth, T is the signal emission period, r is the target distance, c is the speed of light, f0Is the carrier frequency, T is the time, T is the emission period of the first set of sawtooth signals, τdFor the target echo delay, i represents the ith transmit period.
The transmitting signal in the step one is sawtooth wave of LFMCW, and the mathematical expression of the radar transmitting signal is;
in the formula A0To transmit signal amplitude, f0Mu is the slope of the sawtooth wave, T is the transmission period of the sawtooth wave, and rect () is a window function.
From this, an expression for the corresponding echo signal can be written:
in the formula
(R (t) is an expression in the formula x), and σ is a constant related to the reflection coefficient of a target aircraft.
The difference frequency signal of the LFMCW SAR is formed at the front end of the receiver, and after the difference frequency signal of one period is subjected to band-pass filtering, the difference frequency signal can be expressed as:
mu is the frequency modulation rate of the distance direction, and A is the difference frequency signal amplitude.
The third step specifically comprises the following steps:
3.1) carrying out phase compensation and beam forming on the intermediate frequency domain signals, and virtualizing the array signals into a 1 x 32 linear array after carrying out phase compensation. The wave path difference between two adjacent antennas is d sin theta, in the array antenna with four transmitting and eight receiving, the wave path difference between the virtual receiving antennas 4n and 4n +1 is not equal to d sin theta in the actual situation, and phase compensation is needed to change the array into a uniform linear array. And (3) performing phase compensation on the signals:
YVFFC＝T⊙YVFF(5)；
wherein the content of the first and second substances,
YVFFcomplex vector of frequency spectrum unit where target is located:
taking virtual receiving antennas 4 and 5 as an example, the phases of virtual antennas 4, 5, 6 are respectively
We can get the phase difference: delta phi1＝φ5-φ4＝α+β，Δφ2＝φ6-φ5α is the phase difference caused by the antenna spacing, β is the phase difference caused by other factors, so the compensated phase is:
the virtual array is shown in fig. 4.
And 3.2) forming narrow beam receiving for the array receiving signals by adopting a windowing digital beam forming technology, so that clutter interference signals can be inhibited while array gain is obtained, and the target detection probability is improved.
Suppose the beam center azimuth is θ0Considering the transmitting and receiving array structure of the system, the space domain steering vector is as follows:
the conventional non-adaptive beam output signal can be obtained by weighted summation of the signals of 4 × 8 virtual receiving antenna elements:
Z＝(w⊙as(θ0))HYVFFC(7)；
in the formula, H represents conjugate transpose, and the window function w is NtNr× 1, data weighting providing angular domain sidelobe suppression, steering vector as(θ0) Provide for the signal from theta0The maximum coherent accumulation of the direction signals carries out beam forming on all the distance-speed units to obtain
Fig. 5 and fig. 6 are a time domain diagram of data and a diagram of performing fast time dimension FFT and beamforming, respectively, and it can be seen that the signal is completely submerged in noise before signal preprocessing, and the signal-to-noise ratio is significantly improved after preprocessing.
The fourth step specifically comprises the following steps:
4.1) carrying out constant false alarm detection on the target, and carrying out signal detection by adopting an improved CFAR algorithm of a unit average selection criterion. The CFAR detection calculation amount for all the distance-speed units is large, whether the amplitude value of the distance unit is an area peak value is judged before CFAR detection, so that processing of useless signals can be avoided, and a CFAR detection schematic diagram is shown in FIG. 9; input cell signalIs Zc＝Z⊙Z*And the symbol denotes the conjugate of the vector. Will ZcComparing the value of each distance-speed unit with a threshold value, and if the value is greater than the threshold value, determining that a target exists at the point; wherein the threshold product factor calculation formula is:
in the formula NcIs the number of units, pfaIs the false alarm probability.
The constant false alarm detection comprises the following specific steps:
1. number of protection units G c2, number of reference units Nc＝32；
2. According to formula zm＝z⊙z*Calculating the square of the amplitude module value of each point of the frequency spectrum;
3. detecting and calculating the j unit
Of the j-17 th to j-2 th units x1And the mean x of the j +2 th to j +17 th cells2If, if
The point is considered to be targeted. For edge data detection, if j < 17, then the mean is calculated over all reference cells.
Fig. 7 shows the simulation result of CFAR detection.
4.2) carrying out Capon method angle measurement in the altitude angle dimension, and traversing the range to select the angle range in which the beam forming gain reaches the maximum value so as to reduce the calculated amount and obtain the estimated value angle _ E of the altitude angle. The data of the altitude angle dimension are weighted and summed, the weight is a guide vector written by the altitude angle estimation value, and then the shortest distance between the target and the radar is estimated by using the following formula
Wherein
As an estimate of the target-to-radar distance, fmaxThe frequency represented by the peak value of the signal after the beam forming and the CFAR detection;
will be provided with
Carry-in (4) to obtain approximate azimuthal frequency modulation
And finally, carrying out azimuth compression to image the target.
Fig. 8 is an image of the final SAR of the target after the distance and azimuth compression, and it can be seen that the target can be clearly distinguished from the noise, the imaging effect is obvious, and the parameter estimation also achieves a certain accuracy, the estimated altitude angle is 0.675rad, and the error between the distance 68.2m and the actual result is within a controllable range, which illustrates the correctness of the method.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, but any modifications or equivalent variations made according to the technical spirit of the present invention are within the scope of the present invention as claimed.
Claims (2)
1. A defense method for an anti-unmanned aerial vehicle based on a synthetic aperture radar comprises the following steps, and is characterized in that:
the method comprises the following steps: the mechanical turntable carrying antenna of the anti-unmanned aerial vehicle defense device based on the synthetic aperture radar performs uniform circular motion at an angular velocity omega, 24-hour uninterrupted monitoring of the whole airspace is realized by transmitting multi-frequency signals through 360-degree circular scanning, and the antenna receives echo signals, performs beat signal processing and transmits the echo signals to a signal processing module for processing;
step two: taking the real part of the obtained difference frequency signal to perform Fast Fourier Transform (FFT) in the distance direction, and performing equivalent to distance direction compression;
step three: performing phase compensation and beam forming pretreatment on the data obtained in the step two, and performing NtHair NrThe receiving antenna is equivalent to 1 × NtNrWhile improving the signal-to-noise ratio, wherein NrFor receiving the number of antennas, NtThe number of transmitting antennas; the third step specifically comprises the following steps:
3.1) carrying out phase compensation and beam forming on the intermediate frequency domain signals, virtualizing the array signals into a linear array after carrying out phase compensation, wherein the wave path difference between two adjacent antennas is d sin theta, the wave path difference between the virtual receiving antennas 4n and 4n +1 is not equal to d sin theta, and phase compensation is required to be carried out to change the array signals into a uniform linear array;
receiving signal complex vector Y of frequency spectrum unit where target is locatedVFFCarrying out phase compensation to obtain a compensated received signal YVFFC：YVFFC＝T⊙YVFF；
3.2) forming narrow beam receiving signals by adopting a windowing digital beam forming technology on the array receiving signals, so that clutter interference signals can be suppressed while array gain is obtained, and the target detection probability is improved;
suppose the beam center azimuth is θ0Considering the transmitting and receiving array structure, the space-domain steering vector is:
by pairing Nt×NrThe signals of the array elements of the virtual receiving antenna are weighted and summed, and the output signal of the conventional non-adaptive wave beam is Z (w ⊙ a)s(θ0))HYVFFC
In the formula, H represents conjugate transpose, and the window function w is NtNr× 1, data weighting providing angular domain sidelobe suppression, steering vector as(θ0) Provide for the signal from theta0The maximum coherent accumulation of the direction signals carries out beam forming on all the distance-speed units to obtain
Step four: performing CFAR (constant false alarm rate) detection, namely constant false alarm rate detection, on the data obtained in the step three, screening signals to reduce data volume, then estimating the distance of the target, and estimating the altitude angle of the target by using a Capon method;
the fourth step specifically comprises the following steps:
performing constant false alarm detection on the target, and performing signal detection by adopting an improved CFAR algorithm of a unit average selection criterion; the CFAR detection calculation amount of all the distance-speed units is large, whether the amplitude value of the distance-speed unit is an area peak value or not is judged before the CFAR detection, and the processing of useless signals can be avoided;
input cell signal is Zc＝Z⊙Z*The symbol denotes the conjugate of the vector, and Z iscComparing the value of each distance-speed unit with a threshold value, and if the value is greater than the threshold value, determining that a target exists at the point;
wherein the threshold product factor calculation formula is:
in the formula NcIs the number of units, pfaIs the false alarm probability;
the method comprises the steps of measuring angles in a Capon method in an altitude angle dimension, traversing a range to select an angle range with a beam forming gain reaching the maximum value so as to reduce the calculated amount, obtaining an estimated value angle _ E of the altitude angle, carrying out weighted summation on data in the altitude angle dimension, wherein weight is a guide vector written by the estimated value of the altitude angle, and estimating the shortest distance between a target and a radar by using the following formula
Wherein
Is the shortest distance of the target to the radar, fmaxThe frequency represented by the peak value of the signal after the beam forming and the CFAR detection;
will be provided with
Substitution into
Wherein Sm(T) represents a signal obtained by band-pass filtering a periodic difference frequency signal, mu is the frequency modulation rate of the distance direction, A is the amplitude of the difference frequency signal, T is the signal emission period, f0Is the carrier frequency, t is time;
obtaining approximate azimuth frequency modulation rate
And after interpolation distance migration correction is carried out, azimuth compression is carried out to image the target.
2. The method of claim 1, wherein the method comprises the following steps: the anti-unmanned aerial vehicle defense device based on the synthetic aperture radar comprises a signal transmitting and receiving module and a signal processing module;
the signal transmitting and receiving module comprises a mechanical turntable, a 4-transmitting 8-receiving millimeter wave antenna and a signal transmitting and receiving chip, wherein the mechanical turntable carries the millimeter wave antenna to perform 360-degree annular scanning, the signal transmitting and receiving chip generates an excitation signal to control the antenna to transmit linear frequency modulation continuous waves and receive echo signals, and meanwhile, the signals subjected to difference frequency processing are sent to the signal processing module;
the signal processing module comprises distance direction compression, parameter estimation and SAR imaging, and the distance direction compression reduces the calculated amount of subsequent processing signals; obtaining distance and altitude angle information of the target by parameter estimation; and SAR imaging is carried out to obtain azimuth information of the target and a track of the target motion.
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