WO2019183750A1 - 一种惯量传感器的校正方法、装置、终端设备和存储介质 - Google Patents

一种惯量传感器的校正方法、装置、终端设备和存储介质 Download PDF

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Publication number
WO2019183750A1
WO2019183750A1 PCT/CN2018/080472 CN2018080472W WO2019183750A1 WO 2019183750 A1 WO2019183750 A1 WO 2019183750A1 CN 2018080472 W CN2018080472 W CN 2018080472W WO 2019183750 A1 WO2019183750 A1 WO 2019183750A1
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Prior art keywords
deviation
value
inertia
inertia sensor
target
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PCT/CN2018/080472
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English (en)
French (fr)
Inventor
郗宏涛
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深圳市锐明技术股份有限公司
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Application filed by 深圳市锐明技术股份有限公司 filed Critical 深圳市锐明技术股份有限公司
Priority to CN201880000222.XA priority Critical patent/CN108496059B/zh
Priority to PCT/CN2018/080472 priority patent/WO2019183750A1/zh
Publication of WO2019183750A1 publication Critical patent/WO2019183750A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices

Definitions

  • the present invention relates to the field of sensor technologies, and in particular, to a method, an apparatus, a terminal device and a computer storage medium for correcting an inertia sensor.
  • Inertia sensors are widely used in the field of vehicle security, and the accuracy of their data plays an important role in vehicle attitude analysis.
  • the inertia sensor performs a manual static calibration after the first installation, and the subsequent data correction is performed according to the deviation obtained from the first calibration.
  • the installation angle and installation position of the inertia sensor will change, which will cause the actual data deviation to change.
  • the data will be corrected.
  • the deviation of the values is large, which makes the data accuracy of the entire inertial sensor system decrease.
  • embodiments of the present invention provide a method, an apparatus, a terminal device, and a computer storage medium for correcting an inertia sensor, which can improve data accuracy of an inertial sensor system.
  • a first aspect of the embodiments of the present invention provides a method for correcting an inertia sensor, including:
  • Correcting the data output by the inertia sensor according to the target deviation, and the initial value of the target deviation is a deviation value obtained by the first calibration after the inertia sensor is installed;
  • the target deviation is updated using the calculated deviation value.
  • a second aspect of the embodiments of the present invention provides a calibration apparatus for an inertia sensor, including:
  • a data correction module configured to correct data output by the inertia sensor according to the target deviation, where the initial value of the target deviation is a deviation value obtained by the first calibration after the inertia sensor is installed;
  • a target data acquisition module configured to acquire target data output by the inertia sensor when the inertia sensor is switched from a motion state to a stationary state
  • a deviation value calculation module configured to calculate a deviation value between the target data and a preset theoretical inertia value, wherein the theoretical inertia value is a inertia value that the inertia sensor should theoretically output when stationary;
  • a deviation update module configured to update the target deviation by using the calculated deviation value.
  • a third aspect of an embodiment of the present invention provides a terminal device including a memory, a processor, and a computer program stored in the memory and operable on the processor, when the processor executes the computer program
  • the steps of the correction method of the inertia sensor as provided in the first aspect of the embodiment of the present invention are achieved.
  • a fourth aspect of the embodiments of the present invention provides a computer readable storage medium storing a computer program, the computer program being executed by a processor to implement the first aspect of the embodiment of the present invention The steps of the correction method of the inertia sensor.
  • the data output by the inertia sensor is corrected according to the target deviation, and the initial value of the target deviation is a deviation value obtained by the first calibration after the inertia sensor is installed; when the inertia sensor is switched from the motion state to the motion state In a stationary state, acquiring target data output by the inertia sensor; calculating a deviation value between the target data and a preset theoretical inertia value, the theoretical inertia value being theoretically outputted when the inertia sensor is stationary Inertia value; the target deviation is updated with the calculated deviation value.
  • the inertia sensor Assuming that the inertia sensor is mounted on a moving vehicle, during the stop of the vehicle, the inertia sensor can be detected to switch from the moving state to the stationary state. At this time, the target data output by the inertia sensor is collected, and then the target data and the target data are calculated. The deviation value between the theoretical inertia values, and the calculated deviation value is used to update the target deviation for data correction. Obviously, the deviation for data correction is updated in real time every time the vehicle stops, which can effectively solve the problem of inaccurate deviation caused by the change of the actual deviation after the traditional single static correction, thereby ensuring the corrected data and The deviation of the true value is small, and the data accuracy of the inertia sensor system is improved.
  • FIG. 1 is a flow chart of a first embodiment of a method for correcting an inertia sensor according to an embodiment of the present invention
  • FIG. 2 is a flow chart of a second embodiment of a method for correcting an inertia sensor according to an embodiment of the present invention
  • FIG. 3 is a structural diagram of an embodiment of a calibration apparatus for an inertia sensor according to an embodiment of the present invention
  • FIG. 4 is a schematic diagram of a terminal device according to an embodiment of the present invention.
  • a first embodiment of a method for correcting an inertia sensor according to an embodiment of the present invention includes:
  • the inertia sensor can be mounted on any moving object (such as a vehicle or a ship) for detecting the inertia data of the moving object.
  • the data collected and output by the inertia sensor is corrected according to the target deviation, where the target deviation is a variable whose initial value is the deviation value obtained by the first calibration after the inertia sensor is installed, and the target deviation is updated by the following steps 102 to 104.
  • the target deviation is used to correct the data output by the inertia sensor.
  • the corrected data is x- ⁇ x, y- ⁇ y. , z- ⁇ z.
  • the target data output by the inertia sensor is acquired.
  • the dynamic state of the inertia sensor is equivalent to the dynamic state of the object to which it is mounted. Therefore, switching the inertia sensor from the moving state to the stationary state is equivalent to switching the installed object from the moving state to the stationary state, such as after the vehicle in motion stops.
  • the target data output by the inertia sensor is collected, where the target data is the original inertia data collected at the current time, that is, the uncorrected data.
  • the inertia sensor is installed on a vehicle, and whether the inertia sensor is in a stationary state can be determined by the following three methods.
  • Method 1 acquiring satellite navigation positioning information of the vehicle; determining a speed of the vehicle according to the satellite navigation positioning information; and determining that the inertia sensor is stationary if the speed of the vehicle is maintained at 0 for a second duration status.
  • obtaining real-time GPS positioning information of the vehicle and determining the speed of the vehicle according to the positioning information. If it is determined that the speed of the vehicle is maintained at 0 for a second duration (for example, 5 seconds), it may be determined that the inertia sensor is Stationary state.
  • a second duration for example, 5 seconds
  • Mode 2 Acquire a speed of the vehicle from a transmission system of the vehicle; if the speed of the vehicle is 0, determine that the inertia sensor is in a stationary state.
  • the transmission system of the vehicle itself can output the real-time speed parameter of the vehicle, the speed of the vehicle can be obtained directly from the transmission system of the vehicle; if the acquired vehicle speed is 0, it is determined that the inertia sensor is in a stationary state.
  • Mode 3 If it is detected that the fluctuation range of the data output by the inertia sensor in the third duration is less than a preset threshold, it is determined that the inertia sensor is in a stationary state.
  • the above three methods may also be used in combination, for example, by using mode 2+ mode 3, or by mode 1+ mode 3.
  • the theoretical inertia value here is the inertia value that the inertia sensor should theoretically output when it is stationary.
  • the calculated deviation values are x-X, y-Y, z-Z.
  • the target deviation is updated by using the deviation value, that is, the original deviation value of the target deviation is replaced with the calculated current time. Deviation.
  • the data output by the inertia sensor is corrected based on the updated target deviation.
  • a new deviation value is calculated, and the calculated deviation value is used to update the target deviation.
  • the target deviation is updated every time the vehicle stops, which is equivalent to adjusting the target deviation multiple times during the driving process of the vehicle, thereby improving the target deviation and the corrected data. accuracy.
  • the data output by the inertia sensor is corrected according to the target deviation, and the initial value of the target deviation is a deviation value obtained by the first calibration after the inertia sensor is installed; when the inertia sensor is switched from the motion state to the motion state In a stationary state, acquiring target data output by the inertia sensor; calculating a deviation value between the target data and a preset theoretical inertia value, the theoretical inertia value being theoretically outputted when the inertia sensor is stationary Inertia value; the target deviation is updated with the calculated deviation value.
  • the inertia sensor Assuming that the inertia sensor is mounted on a moving vehicle, during the stop of the vehicle, the inertia sensor can be detected to switch from the moving state to the stationary state. At this time, the target data output by the inertia sensor is collected, and then the target data and the target data are calculated. The deviation value between the theoretical inertia values, and the calculated deviation value is used to update the target deviation for data correction. Obviously, the deviation for data correction is updated in real time every time the vehicle stops, which can effectively solve the problem of inaccurate deviation caused by the change of the actual deviation after the traditional single static correction, thereby ensuring the corrected data and The deviation of the true value is small, and the data accuracy of the inertia sensor system is improved.
  • a second embodiment of a method for correcting an inertia sensor according to an embodiment of the present invention includes:
  • Step 201 is the same as step 101. For details, refer to the related description of step 101.
  • Step 202 collects a plurality of data as compared to collecting data once in step 102.
  • the data output by the inertia sensor is collected multiple times in the first time period to obtain multiple sets of inertia data. For example, 100 times of inertia sensor output data is acquired in 1 second to obtain 100 sets of inertia data.
  • each set of inertia data can be expressed as ⁇ x, y, z ⁇ .
  • the average or maximum value of the plurality of sets of inertia data is determined as the target data.
  • the definition and function of the target data are the same as the target data in step 102.
  • the target data and the theoretical inertia value are compared to obtain a first deviation value, where the theoretical inertia value is the same as the theoretical inertia value definition in step 103.
  • the historical deviation value including an initial value of the target deviation and a deviation value after each update. For example, if the target deviation is updated once before the current time, the historical deviation value includes the initial value (the deviation value obtained by the first correction after the inertia sensor is installed) and the deviation value obtained after the update; a total deviation value; When the current time is updated 10 times, the historical deviation value includes 11 initial values and 10 updated deviation values. The updated deviation value is recorded and stored each time the target deviation is updated to form the historical deviation value.
  • step 205 may specifically include:
  • the number of recorded historical deviation values is less than or equal to a preset first quantity (such as 20), and if the first quantity is less than or equal to the target deviation And all the historical deviation values of the historical deviation values of the target deviations are the first number of historical deviation values that are closest to the current time. Assuming that the first quantity is 20, if the target deviation is updated 10 times, that is, the number of historical deviation values is 11, the 11 historical deviation values are all acquired; if the target deviation is updated 30 times, that is, the historical deviation If the number of values is 31, the 20 historical deviation values of the 31 historical deviation values that are the latest update time from the current time, that is, the deviation values obtained from the 11th to 30th update, are obtained.
  • a preset first quantity such as 20
  • the historical deviation value of the earlier update time can be ignored, thereby reducing the calculation amount of the subsequent steps.
  • the historical deviation value of the earlier update time can also be deleted to reduce the occupied storage space.
  • Steps 205 and 206 After acquiring the historical deviation value of the target deviation, the average value of the first deviation value and the acquired historical deviation value is determined as a deviation value between the target data and the theoretical inertia value. Steps 205 and 206 perform a process of deviation statistics. By statistically updating the deviation values used and obtaining the average value, the actual deviation of the inertia sensor can be more truly reflected, thereby obtaining a more accurate update. The deviation of the target deviation.
  • the average value may be removed and then averaged, or other data processing methods in data statistics and analysis may be used.
  • the target deviation is updated by using the deviation value.
  • the data output by the inertia sensor is corrected based on the updated target deviation.
  • the data output by the inertia sensor is corrected according to the target deviation; when the inertia sensor is switched from the motion state to the stationary state, the data output by the inertia sensor is collected multiple times in the first time period to obtain a plurality of sets of inertia data; determining an average value or a maximum value of the plurality of sets of inertia data as target data; performing difference between the target data and the theoretical inertia value to obtain a first deviation value; and obtaining a historical deviation value of the target deviation Determining an average value of the first deviation value and the acquired historical deviation value as a deviation value between the target data and the theoretical inertia value; using between the target data and the theoretical inertia value The deviation value updates the target deviation.
  • the present embodiment determines the target data by acquiring multiple sets of inertia data and obtaining an average value or a maximum value, and can acquire original inertia data closer to the true value;
  • the statistical method can obtain a more accurate deviation value for updating the target deviation, that is, obtain a more accurate target deviation, thereby further improving the data accuracy of the inertia sensor system.
  • a data recording method has been mainly described above, and a data recording system will be described below.
  • the above mainly describes a correction method of the inertia sensor, and a correction device of the inertia sensor will be described below.
  • an embodiment of a calibration apparatus for an inertia sensor includes:
  • the data correction module 301 is configured to correct data output by the inertia sensor according to the target deviation, where the initial value of the target deviation is a deviation value obtained by the inertia sensor after being installed for the first time;
  • the target data collection module 302 is configured to collect target data output by the inertia sensor when the inertia sensor is switched from a motion state to a stationary state;
  • the deviation value calculation module 303 is configured to calculate a deviation value between the target data and a preset theoretical inertia value, where the theoretical inertia value is a inertia value that the inertia sensor should theoretically output when stationary;
  • the deviation update module 304 is configured to update the target deviation by using the calculated deviation value.
  • target data collection module 302 can include:
  • a data acquisition unit configured to acquire data output by the inertia sensor multiple times in a first time period to obtain multiple sets of inertia data
  • a data determining unit configured to determine an average value or a maximum value of the plurality of sets of inertia data as the target data.
  • the deviation value calculation module 303 may include:
  • a difference unit configured to perform a difference between the target data and the theoretical inertia value to obtain a first deviation value
  • a historical deviation value obtaining unit configured to acquire a historical deviation value of the target deviation, where the historical deviation value includes an initial value of the target deviation and a deviation value after each update;
  • the deviation value determining unit is configured to determine an average value of the first deviation value and the acquired historical deviation value as a deviation value between the original data and the theoretical inertia value.
  • An embodiment of the present invention further provides a terminal device, including a memory, a processor, and a computer program stored in the memory and operable on the processor, where the processor implements the computer program as shown in FIG. 1 Or the steps of the calibration method of any one of the inertia sensors shown in FIG.
  • the embodiment of the present invention further provides a computer readable storage medium, where the computer readable storage medium stores a computer program, and when the computer program is executed by the processor, implements any inertial sensor as shown in FIG. 1 or FIG. The steps of the calibration method.
  • FIG. 4 is a schematic diagram of a terminal device according to an embodiment of the present invention.
  • the terminal device 4 of this embodiment includes a processor 40, a memory 41, and a computer program 42 stored in the memory 41 and operable on the processor 40.
  • the steps in the embodiment of the method for correcting the respective inertia sensors described above when the processor 40 executes the computer program 42 such as steps 101 to 104 shown in FIG.
  • the processor 40 executes the computer program 42 the functions of the modules/units in the above various device embodiments are implemented, such as the functions of the modules 301 to 304 shown in FIG.
  • the computer program 42 can be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40 to complete the present invention.
  • the one or more modules/units may be a series of computer program instruction segments capable of performing a particular function, the instruction segments being used to describe the execution of the computer program 42 in the terminal device 4.
  • the terminal device 4 may be a computing device such as various types of mobile phones, desktop computers, notebooks, palmtop computers, and cloud servers.
  • the terminal device may include, but is not limited to, a processor 40 and a memory 41. It will be understood by those skilled in the art that FIG. 4 is only an example of the terminal device 4, does not constitute a limitation of the terminal device 4, may include more or less components than those illustrated, or combine some components, or different components.
  • the terminal device 4 may further include an input/output device, a network access device, a bus, and the like.
  • the so-called processor 40 can be a central processing unit (Central Processing Unit, CPU), can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.
  • the general purpose processor may be a microprocessor or the processor or any conventional processor or the like.
  • the memory 41 may be an internal storage unit of the terminal device 4, such as a hard disk or a memory of the terminal device 4.
  • the memory 41 may also be an external storage device of the terminal device 4, such as a plug-in hard disk equipped on the terminal device 4, a smart memory card (SMC), and a secure digital (SD). Card, flash card (Flash Card) and so on. Further, the memory 41 may also include both an internal storage unit of the terminal device 4 and an external storage device.
  • the memory 41 is used to store the computer program and other programs and data required by the terminal device.
  • the memory 41 can also be used to temporarily store data that has been output or is about to be output.
  • each functional unit and module described above is exemplified. In practical applications, the above functions may be assigned to different functional units as needed.
  • the module is completed by dividing the internal structure of the device into different functional units or modules to perform all or part of the functions described above.
  • Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit, and the integrated unit may be hardware.
  • Formal implementation can also be implemented in the form of software functional units.
  • the specific names of the respective functional units and modules are only for the purpose of facilitating mutual differentiation, and are not intended to limit the scope of protection of the present application.
  • the disclosed apparatus and method may be implemented in other manners.
  • the system embodiment described above is merely illustrative.
  • the division of the module or unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be used. Combinations can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in electrical, mechanical or other form.
  • 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, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the present invention implements all or part of the processes in the foregoing embodiments, and may also be completed by a computer program to instruct related hardware.
  • the computer program may be stored in a computer readable storage medium. The steps of the various method embodiments described above may be implemented when the program is executed by the processor.
  • the computer program comprises computer program code, which may be in the form of source code, object code form, executable file or some intermediate form.
  • the computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard drive, a magnetic disk, an optical disk, a computer memory, a read only memory (ROM, Read-Only) Memory), random access memory (RAM, Random) Access Memory), electrical carrier signals, telecommunications signals, and software distribution media.
  • ROM Read Only memory
  • RAM Random Access Memory
  • electrical carrier signals telecommunications signals
  • telecommunications signals and software distribution media. It should be noted that the content contained in the computer readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in a jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, computer readable media It does not include electrical carrier signals and telecommunication signals.

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Abstract

一种惯量传感器的校正方法，包括：根据目标偏差对惯量传感器输出的数据进行校正（101），目标偏差的初始值为惯量传感器安装后首次校正得到的偏差值；当惯量传感器从运动状态切换至静止状态时，采集惯量传感器输出的目标数据（102）；计算目标数据与预设的理论惯量值之间的偏差值（103）；用计算得到的偏差值更新目标偏差（104）。假设将惯量传感器安装在行驶的车辆上，则在车辆每次停车时都会实时更新一次用于数据校正的偏差，这样能够有效解决单次静态校正后由于实际偏差产生变化引起的偏差不准的问题，从而提高惯量传感器***的数据准确性。还提供一种惯量传感器的校正装置、终端设备和计算机存储介质。

Description

一种惯量传感器的校正方法、装置、终端设备和存储介质 技术领域
本发明涉及传感器技术领域，尤其涉及一种惯量传感器的校正方法、装置、终端设备和计算机存储介质。
 背景技术
惯量传感器广泛应用于车载安防领域，其数据的准确性对于车辆的姿态分析具有重要作用。惯量传感器在首次安装后会进行一次手动的静态校正，后续都是按照首次校正得到的偏差进行数据校正。然而，随着车辆颠簸，惯量传感器的安装角度和安装位置会出现变动，这样会导致实际的数据偏差产生变化，此时若仍然使用首次校正得到的偏差进行数据校正将导致校正后的数据与真实值的偏差较大，使得整个惯量传感器***的数据准确性下降。
 技术问题
有鉴于此，本发明实施例提供了一种惯量传感器的校正方法、装置、终端设备和计算机存储介质，能够提高惯量传感器***的数据准确性。
 技术解决方案
本发明实施例的第一方面提供了一种惯量传感器的校正方法，包括：
根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；
当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；
计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；
采用计算得到的偏差值更新所述目标偏差。
本发明实施例的第二方面提供了一种惯量传感器的校正装置，包括：
数据校正模块，用于根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；
目标数据采集模块，用于当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；
偏差值计算模块，用于计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；
偏差更新模块，用于采用计算得到的偏差值更新所述目标偏差。
本发明实施例的第三方面提供了一种终端设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如本发明实施例的第一方面提供的惯量传感器的校正方法的步骤。
本发明实施例的第四方面提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如本发明实施例的第一方面提供的惯量传感器的校正方法的步骤。
 有益效果
在本发明实施例中，根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；用计算得到的偏差值更新所述目标偏差。假设将惯量传感器安装在行驶的车辆上，则在该车辆的每次停车过程中，能够检测到惯量传感器从运动状态切换至静止状态，此时采集惯量传感器输出的目标数据，然后计算目标数据和理论惯量值之间的偏差值，用计算得到的偏差值更新用于数据校正的目标偏差。显然，在车辆每次停车时都会实时更新一次用于数据校正的偏差，这样能够有效解决传统的单次静态校正后由于实际偏差产生变化引起的偏差不准的问题，从而保证校正后的数据与真实值的偏差较小，提高惯量传感器***的数据准确性。
 附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例提供的一种惯量传感器的校正方法的第一个实施例的流程图；
图2是本发明实施例提供的一种惯量传感器的校正方法的第二个实施例的流程图；
图3是本发明实施例提供的一种惯量传感器的校正装置的一个实施例的结构图；
图4是本发明实施例提供的一种终端设备的示意图。
 本发明的实施方式
以下描述中，为了说明而不是为了限定，提出了诸如特定***结构、技术之类的具体细节，以便透彻理解本发明实施例。然而，本领域的技术人员应当清楚，在没有这些具体细节的其它实施例中也可以实现本发明。在其它情况中，省略对众所周知的***、装置、电路以及方法的详细说明，以免不必要的细节妨碍本发明的描述。
为了说明本发明所述的技术方案，下面通过具体实施例来进行说明。
实施例1
请参阅图1，本发明实施例中一种惯量传感器的校正方法的第一个实施例包括：
101、根据目标偏差对惯量传感器输出的数据进行校正；
在本发明实施例中，惯量传感器可以安装在任意运动物体（比如车辆、轮船）上，用于检测该运动物体的惯量数据。惯量传感器采集并输出的数据根据目标偏差进行校正，这里的目标偏差是一个变量，其初始值为所述惯量传感器安装后首次校正得到的偏差值，目标偏差通过以下步骤102至104进行更新。在惯量传感器安装完毕后，直至整个数据采集过程的结束，均采用该目标偏差对惯量传感器输出的数据进行校正。具体的，以三轴惯量传感器为例，若传感器输出的数据为x，y，z，目标偏差为△x，△y，△z，则校正后的数据为x-△x，y-△y，z-△z。
102、当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；
当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据。惯量传感器的动静状态等同于其所安装的物体的动静状态，故惯量传感器从运动状态切换至静止状态等同于其所安装的物体从运动状态切换至静止状态，比如行驶中的车辆停车后。当判断惯量传感器处于静止状态时，采集所述惯量传感器输出的目标数据，这里的目标数据为当前时刻采集到的原始惯量数据，即未校正的数据。
具体的，所述惯量传感器安装于车辆上，所述惯量传感器是否处于静止状态可以通过以下3种方式判断。
方式1：获取所述车辆的卫星导航定位信息；根据所述卫星导航定位信息确定所述车辆的速度；若所述车辆的速度在第二时长内保持为0，则判定所述惯量传感器处于静止状态。
比如，获取该车辆的实时GPS定位信息，根据该定位信息可以确定该车辆的速度，若确定该车辆的速度在第二时长（比如5秒）内保持为0，则可以判定所述惯量传感器处于静止状态。
方式2：从所述车辆的传动***获取所述车辆的速度；若所述车辆的速度为0，则判定所述惯量传感器处于静止状态。
由于车辆的传动***本身可以输出该车辆的实时速度参数，因此可以直接从车辆的传动***获取所述车辆的速度；若获取到的车辆速度为0，则判定所述惯量传感器处于静止状态。
方式3：若检测到所述惯量传感器输出的数据在第三时长内的波动范围小于预设的阈值，则判定所述惯量传感器处于静止状态。
当车辆运动（非保持匀速运动）时，其惯量值变化较大，即惯量传感器输出的数据的波动范围较大。当车辆静止或持续处于匀速运动时，其惯量值理论上不变，而实际上的变化幅度很小，因此若检测到所述惯量传感器输出的数据在第三时长内（比如5秒）的波动范围小于预设的阈值，则可以判定所述惯量传感器处于静止状态（基于在实际情况下车辆很难处于绝对的匀速运动状态）。
进一步的，为了提高判断惯量传感器是否处于静止状态的准确性，以上3种方式也可以结合使用，比如采用方式2+方式3进行判断，或采用方式1+方式3进行判断。
103、计算所述目标数据与预设的理论惯量值之间的偏差值；
在采集到所述目标数据之后，计算所述目标数据与预设的理论惯量值之间的偏差值。这里的理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值，比如对于静态平稳的三轴惯量传感器，其理论惯量值为X=0，Y=0，Z=-1。
假设所述目标数据为x，y，z，对应的理论惯量值为X，Y，Z，则计算得到的偏差值为x-X，y-Y，z-Z。
104、采用计算得到的偏差值更新所述目标偏差。
在计算得到所述目标数据与预设的理论惯量值之间的偏差值之后，采用该偏差值更新所述目标偏差，即在当前时刻将所述目标偏差的原偏差值替换成该计算得到的偏差值。在目标偏差更新后，根据更新后的目标偏差对惯量传感器输出的数据进行校正。显然，当惯量传感器每次从运动状态切换至静止状态时，都会计算一次新的偏差值，并用计算得到的偏差值对目标偏差进行更新。假设将惯量传感器安装于行驶的车辆上，则在该车辆每次停车时都会更新一次目标偏差，相当于在车辆的行车过程中多次对目标偏差进行调整，从而提高目标偏差以及校正后数据的准确性。
在本发明实施例中，根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；用计算得到的偏差值更新所述目标偏差。假设将惯量传感器安装在行驶的车辆上，则在该车辆的每次停车过程中，能够检测到惯量传感器从运动状态切换至静止状态，此时采集惯量传感器输出的目标数据，然后计算目标数据和理论惯量值之间的偏差值，用计算得到的偏差值更新用于数据校正的目标偏差。显然，在车辆每次停车时都会实时更新一次用于数据校正的偏差，这样能够有效解决传统的单次静态校正后由于实际偏差产生变化引起的偏差不准的问题，从而保证校正后的数据与真实值的偏差较小，提高惯量传感器***的数据准确性。
实施例2
请参阅图2，本发明实施例中一种惯量传感器的校正方法的第二个实施例包括：
201、根据目标偏差对惯量传感器输出的数据进行校正；
步骤201与步骤101相同，具体可参照步骤101的相关说明。
202、当所述惯量传感器从运动状态切换至静止状态时，在第一时长内多次采集所述惯量传感器输出的数据，得到多组惯量数据；
与步骤102中采集一次数据相比，步骤202采集了多次数据。当检测到惯量传感器从运动状态切换至静止状态时，在第一时长内多次采集所述惯量传感器输出的数据，得到多组惯量数据。比如，在1秒内采集100次惯量传感器输出的数据，得到100组惯量数据，对于三轴惯量传感器来说每组惯量数据可以表示为{x，y，z}。
203、将所述多组惯量数据的平均值或最大值确定为目标数据；
在得到多组惯量数据之后，将这多组惯量数据的平均值或最大值确定为目标数据。这里的目标数据的定义和作用与步骤102中的目标数据相同，通过求取平均值或最大值的方式能够获取与真实数值更加接近的原始惯量数据，有利于后续计算更准确的用于更新目标偏差的偏差值。
204、将所述目标数据和理论惯量值作差，得到第一偏差值；
在得到目标数据之后，将将所述目标数据和理论惯量值作差，得到第一偏差值，这里的理论惯量值与步骤103中的理论惯量值定义相同。
205、获取所述目标偏差的历史偏差值；
获取所述目标偏差的历史偏差值，所述历史偏差值包括所述目标偏差的初始值和每次更新后的偏差值。比如，若目标偏差在当前时间之前更新了一次，则历史偏差值包括初始值（惯量传感器安装后首次校正得到的偏差值）和该次更新后得到的偏差值共2个偏差值；若目标偏差在当前时间之前更新了10次，则历史偏差值包括初始值和10次更新的偏差值共11个偏差值。在目标偏差每次更新时，将更新的偏差值记录并存储，形成所述历史偏差值。
进一步的，步骤205具体可以包括：
（1）判断所述历史偏差值的数量是否小于或等于预设的第一数量，若是则执行步骤（2），否则执行步骤（3）；
（2）获取所述目标偏差的所有历史偏差值；
（3）获取所述目标偏差的历史偏差值中对应的更新时间距离当前时间最近的第一数量的历史偏差值。
对于上述步骤（1）至（3），首先判断已记录的历史偏差值的数量是否小于或等于预设的第一数量（比如20），若小于或等于该第一数量则获取所述目标偏差的所有历史偏差值；若大于该第一数量则获取所述目标偏差的历史偏差值中对应的更新时间距离当前时间最近的第一数量的历史偏差值。假设第一数量为20，若所述目标偏差更新了10次，即历史偏差值的数量为11，则将这11个历史偏差值全部获取；若所述目标偏差更新了30次，即历史偏差值的数量为31，则获取这31个历史偏差值中更新时间距离当前时间最近的20个历史偏差值，即第11至30次更新得到的偏差值。通过这样设置，当历史偏差值的数量过多时，能够忽略更新时间较早的历史偏差值，从而减小后续步骤的计算量。另外，也可将更新时间较早的历史偏差值删除，以减少占用的存储空间。
206、将所述第一偏差值和获取到的历史偏差值的平均值确定为所述目标数据与所述理论惯量值之间的偏差值；
在获取所述目标偏差的历史偏差值之后，将所述第一偏差值和获取到的历史偏差值的平均值确定为所述目标数据与所述理论惯量值之间的偏差值。步骤205和206进行的是一个偏差统计的过程，通过统计多次更新采用的偏差值并求取平均值的方式，能够更真实地反映惯量传感器的实际偏差情况，从而获取更准确的用于更新目标偏差的偏差值。
可选的，在步骤206中，也可以采用去除最大最小值后再取平均值，或者数据统计与分析中的其它数据处理方式。
207、采用所述目标数据与所述理论惯量值之间的偏差值更新所述目标偏差。
在得到所述目标数据与所述理论惯量值之间的偏差值之后，采用该偏差值更新所述目标偏差。在目标偏差更新后，根据更新后的目标偏差对惯量传感器输出的数据进行校正。
在本发明实施例中，根据目标偏差对惯量传感器输出的数据进行校正；当所述惯量传感器从运动状态切换至静止状态时，在第一时长内多次采集所述惯量传感器输出的数据，得到多组惯量数据；将所述多组惯量数据的平均值或最大值确定为目标数据；将所述目标数据和理论惯量值作差，得到第一偏差值；获取所述目标偏差的历史偏差值；将所述第一偏差值和获取到的历史偏差值的平均值确定为所述目标数据与所述理论惯量值之间的偏差值；采用所述目标数据与所述理论惯量值之间的偏差值更新所述目标偏差。与本发明的第一个实施例相比，本实施例采用获取多组惯量数据并求取平均值或最大值的方式确定目标数据，能够获取与真实数值更加接近的原始惯量数据；而且通过偏差统计的方式，能够获取更准确的用于更新目标偏差的偏差值，即获得更准确的目标偏差，从而进一步提高了惯量传感器***的数据准确性。
应理解，上述各个实施例中各步骤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。
实施例3
上面主要描述了一种数据记录方法，下面将对一种数据记录***进行描述。
上面主要描述了一种惯量传感器的校正方法，下面将对一种惯量传感器的校正装置进行描述。
请参阅图3，本发明实施例中一种惯量传感器的校正装置的一个实施例包括：
数据校正模块301，用于根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；
目标数据采集模块302，用于当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；
偏差值计算模块303，用于计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；
偏差更新模块304，用于采用计算得到的偏差值更新所述目标偏差。
进一步的，所述目标数据采集模块302可以包括：
数据采集单元，用于在第一时长内多次采集所述惯量传感器输出的数据，得到多组惯量数据；
数据确定单元，用于将所述多组惯量数据的平均值或最大值确定为所述目标数据。
进一步的，所述偏差值计算模块303可以包括：
作差单元，用于将所述目标数据和所述理论惯量值作差，得到第一偏差值；
历史偏差值获取单元，用于获取所述目标偏差的历史偏差值，所述历史偏差值包括所述目标偏差的初始值和每次更新后的偏差值；
偏差值确定单元，用于将所述第一偏差值和获取到的历史偏差值的平均值确定为所述原始数据与理论惯量值之间的偏差值。
本发明实施例还提供一种终端设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如图1或图2表示的任意一种惯量传感器的校正方法的步骤。
本发明实施例还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如图1或图2表示的任意一种惯量传感器的校正方法的步骤。
图4是本发明一实施例提供的终端设备的示意图。如图4所示，该实施例的终端设备4包括：处理器40、存储器41以及存储在所述存储器41中并可在所述处理器40上运行的计算机程序42。所述处理器40执行所述计算机程序42时实现上述各个惯量传感器的校正方法的实施例中的步骤，例如图1所示的步骤101至104。或者，所述处理器40执行所述计算机程序42时实现上述各装置实施例中各模块/单元的功能，例如图3所示模块301至304的功能。
所述计算机程序42可以被分割成一个或多个模块/单元，所述一个或者多个模块/单元被存储在所述存储器41中，并由所述处理器40执行，以完成本发明。所述一个或多个模块/单元可以是能够完成特定功能的一系列计算机程序指令段，该指令段用于描述所述计算机程序42在所述终端设备4中的执行过程。
所述终端设备4可以是各种类型的手机、桌上型计算机、笔记本、掌上电脑及云端服务器等计算设备。所述终端设备可包括，但不仅限于，处理器40、存储器41。本领域技术人员可以理解，图4仅仅是终端设备4的示例，并不构成对终端设备4的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件，例如所述终端设备4还可以包括输入输出设备、网络接入设备、总线等。
所称处理器40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。
所述存储器41可以是所述终端设备4的内部存储单元，例如终端设备4的硬盘或内存。所述存储器41也可以是所述终端设备4的外部存储设备，例如所述终端设备4上配备的插接式硬盘，智能存储卡（Smart Media Card, SMC），安全数字（Secure Digital, SD）卡，闪存卡（Flash Card）等。进一步地，所述存储器41还可以既包括所述终端设备4的内部存储单元也包括外部存储设备。所述存储器41用于存储所述计算机程序以及所述终端设备所需的其他程序和数据。所述存储器41还可以用于暂时地存储已经输出或者将要输出的数据。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，仅以上述各功能单元、模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能单元、模块完成，即将所述装置的内部结构划分成不同的功能单元或模块，以完成以上描述的全部或者部分功能。实施例中的各功能单元、模块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，上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。另外，各功能单元、模块的具体名称也只是为了便于相互区分，并不用于限制本申请的保护范围。
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。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述或记载的部分，可以参见其它实施例的相关描述。
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发明的范围。
在本发明所提供的实施例中，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***实施例仅仅是示意性的，例如，所述模块或单元的划分，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讯连接可以是通过一些接口，装置或单元的间接耦合或通讯连接，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，在本发明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。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元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，本发明实现上述实施例方法中的全部或部分流程，也可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一计算机可读存储介质中，该计算机程序在被处理器执行时，可实现上述各个方法实施例的步骤。其中，所述计算机程序包括计算机程序代码，所述计算机程序代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。所述计算机可读介质可以包括：能够携带所述计算机程序代码的任何实体或装置、记录介质、U盘、移动硬盘、磁碟、光盘、计算机存储器、只读存储器（ROM，Read-Only Memory）、随机存取存储器（RAM，Random Access Memory）、电载波信号、电信信号以及软件分发介质等。需要说明的是，所述计算机可读介质包含的内容可以根据司法管辖区内立法和专利实践的要求进行适当的增减，例如在某些司法管辖区，根据立法和专利实践，计算机可读介质不包括是电载波信号和电信信号。
以上所述实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围，均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种惯量传感器的校正方法，其特征在于，包括：
    根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；
    当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；
    计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；
    采用计算得到的偏差值更新所述目标偏差。
  2. 如权利要求1所述的惯量传感器的校正方法，其特征在于，所述采集所述惯量传感器输出的目标数据包括：
    在第一时长内多次采集所述惯量传感器输出的数据，得到多组惯量数据；
    将所述多组惯量数据的平均值或最大值确定为所述目标数据。
  3. 如权利要求1所述的惯量传感器的校正方法，其特征在于，所述计算所述目标数据与预设的理论惯量值之间的偏差值包括：
    将所述目标数据和所述理论惯量值作差，得到第一偏差值；
    获取所述目标偏差的历史偏差值，所述历史偏差值包括所述目标偏差的初始值和每次更新后的偏差值；
    将所述第一偏差值和获取到的历史偏差值的平均值确定为所述目标数据与预设的理论惯量值之间的偏差值。
  4. 如权利要求3所述的惯量传感器的校正方法，其特征在于，所述获取所述目标偏差的历史偏差值包括：
    若所述历史偏差值的数量小于或等于预设的第一数量，则获取所述目标偏差的所有历史偏差值；
    若所述历史偏差值的数量大于所述第一数量，则获取所述目标偏差的历史偏差值中对应的更新时间距离当前时间最近的第一数量的历史偏差值。
  5. 如权利要求1至4中任一项所述的惯量传感器的校正方法，其特征在于，所述惯量传感器安装于车辆上，所述惯量传感器是否处于静止状态通过以下步骤判断：
    获取所述车辆的卫星导航定位信息；
    根据所述卫星导航定位信息确定所述车辆的速度；
    若所述车辆的速度在第二时长内保持为0，则判定所述惯量传感器处于静止状态；
    或者
    从所述车辆的传动***获取所述车辆的速度；
    若所述车辆的速度为0，则判定所述惯量传感器处于静止状态；
    或者
    若检测到所述惯量传感器输出的数据在第三时长内的波动范围小于预设的阈值，则判定所述惯量传感器处于静止状态。
  6. 一种惯量传感器的校正装置，其特征在于，包括：
    数据校正模块，用于根据目标偏差对惯量传感器输出的数据进行校正，所述目标偏差的初始值为所述惯量传感器安装后首次校正得到的偏差值；
    目标数据采集模块，用于当所述惯量传感器从运动状态切换至静止状态时，采集所述惯量传感器输出的目标数据；
    偏差值计算模块，用于计算所述目标数据与预设的理论惯量值之间的偏差值，所述理论惯量值为所述惯量传感器在静止时理论上应当输出的惯量值；
    偏差更新模块，用于采用计算得到的偏差值更新所述目标偏差。
  7. 如权利要求6所述的惯量传感器的校正装置，其特征在于，所述目标数据采集模块包括：
    数据采集单元，用于在第一时长内多次采集所述惯量传感器输出的数据，得到多组惯量数据；
    数据确定单元，用于将所述多组惯量数据的平均值或最大值确定为所述目标数据。
  8. 如权利要求6或7所述的惯量传感器的校正装置，其特征在于，所述偏差值计算模块包括：
    作差单元，用于将所述目标数据和所述理论惯量值作差，得到第一偏差值；
    历史偏差值获取单元，用于获取所述目标偏差的历史偏差值，所述历史偏差值包括所述目标偏差的初始值和每次更新后的偏差值；
    偏差值确定单元，用于将所述第一偏差值和获取到的历史偏差值的平均值确定为所述原始数据与理论惯量值之间的偏差值。
  9. 一种终端设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如权利要求1至5中任一项所述的惯量传感器的校正方法的步骤。
  10. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至5中任一项所述的惯量传感器的校正方法的步骤。
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