CN111189471A - Correction method, correction device and computer storage medium - Google Patents
Correction method, correction device and computer storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a correction method, a correction device and a computer storage medium; wherein the method comprises the following steps: acquiring observed quantity data of an inertial navigation device; obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data; comparing the difference value of the observed quantity with a preset difference parameter threshold; and correcting the observed quantity data of this time according to the comparison result.
Description
Technical Field
The present invention relates to measurement processing technologies, and in particular, to a calibration method, apparatus, and computer storage medium.
Background
The precision of the inertial navigation device is crucial to the influence of system performance, and zero offset is a main error source of the inertial navigation device. The currently general zero offset error correction method for the inertial navigation device mainly comprises the following steps: 1. measuring the zero offset under a static condition, and correcting the offset once again; 2. the method of Kalman filtering is adopted to eliminate zero offset, which is a dynamic adjustment process; 3. and establishing a zero offset error model to eliminate.
However, because the error of the inertial navigation device varies with the working time and the external temperature, a fixed zero offset is not suitable, and therefore the static condition measurement method 1 is not accurate; as for the method 2, on one hand, the kalman filtering algorithm is complex, occupies more resources, has requirements on signal statistical characteristics, and is only required to be a stable signal, and a noise covariance matrix and the like are not well solved; regarding to the 3 rd method, an error model is established, then model parameters are continuously fitted, and finally the zero offset error of the inertial navigation device is eliminated, but actually, the inertial navigation zero offset error source is very complex, and a general error model is difficult to be really fitted in place.
Disclosure of Invention
In order to solve the existing technical problem, embodiments of the present invention provide a calibration method, an apparatus, and a computer storage medium.
In order to achieve the above purpose, the technical solution of the embodiment of the present invention is realized as follows:
the embodiment of the invention provides a correction method, which comprises the following steps:
acquiring observed quantity data of an inertial navigation device;
obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data;
comparing the difference value of the observed quantity with a preset difference parameter threshold;
and correcting the observed quantity data of this time according to the comparison result.
In the above scheme, the method further comprises:
counting the variance value of the observed quantity at intervals of a certain frequency;
determining a preset difference parameter threshold based on the observed quantity variance value;
and the preset difference parameter thresholds of the same observed quantity on different axes are different.
In the foregoing solution, before comparing the difference value of the observed component with a preset difference parameter threshold, the method further includes:
determining the acquisition time corresponding to the observed quantity data;
determining a time period of the acquisition time;
and determining a preset difference parameter threshold matched with the time period based on the time period.
In the foregoing solution, the correcting the observed quantity data of this time according to the comparison result includes:
when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy;
and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
In the foregoing solution, the first correction strategy includes:
determining the weight value of the current observed quantity and the last observed quantity obtained after correction;
taking the combination value of the observed quantity of the current time and the observed quantity of the last time obtained after correction under a certain weight as a correction result for correcting the observed quantity data of the current time;
the second correction policy comprising:
and taking the last observation obtained through correction as a correction result for correcting the observation data of this time.
The embodiment of the invention also provides a correction device, which comprises: the device comprises an acquisition unit, a determination unit, a comparison unit and a correction unit; wherein the content of the first and second substances,
the acquisition unit is used for acquiring observed quantity data of the inertial navigation device;
the determining unit is used for obtaining the observed quantity difference value between the current time and the last time based on the observed quantity data;
the comparison unit is used for comparing the observed component difference value with a preset difference parameter threshold;
and the correction unit is used for correcting the observation quantity data of this time according to the comparison result.
In the above scheme, the apparatus further comprises:
the statistical unit is used for counting the observed quantity variance value at intervals of a certain frequency;
the setting unit is used for determining a preset difference parameter threshold based on the observed quantity variance value;
and the preset difference parameter thresholds of the same observed quantity on different axes are different.
In the foregoing solution, the comparing unit is further configured to:
determining the acquisition time corresponding to the observed quantity data;
determining a time period of the acquisition time;
and determining a preset difference parameter threshold matched with the time period based on the time period.
In the foregoing solution, the correction unit is further configured to:
when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy;
and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
In the foregoing solution, the first correction strategy includes:
determining a weight value of the observation quantity of this time and a weight value of the observation quantity of the last time obtained after correction;
taking the combination value of the observed quantity of the current time and the observed quantity of the last time obtained after correction under a certain weight as a correction result for correcting the observed quantity data of the current time;
the second correction policy comprising:
and taking the last observation obtained through correction as a correction result for correcting the observation data of this time.
Embodiments of the present invention also provide a computer storage medium having computer instructions stored thereon, where the computer instructions, when executed by a processor, implement the steps of the calibration method according to the embodiments of the present invention.
The embodiment of the present invention further provides a server, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the steps of the calibration method according to the embodiment of the present invention are implemented.
According to the technical scheme of the embodiment of the invention, observed quantity data of an inertial navigation device is obtained; obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data; comparing the difference value of the observed quantity with a preset difference parameter threshold; and correcting the observed quantity data of this time according to the comparison result. Therefore, a new zero offset correction method is provided, and the problem of accumulated error caused by the fact that the fixed zero offset does not change along with the time can be avoided; and the operation amount is small, the real-time performance is good, and the scheme is simple and easy to realize.
Drawings
FIG. 1 is a schematic flowchart of a calibration method according to a first embodiment of the present invention;
FIG. 2 is a schematic flowchart of a calibration method according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of a structure of a calibration device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a hardware composition structure of the calibration apparatus according to the embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Example one
The embodiment of the invention provides a correction method. Fig. 1 is a schematic flowchart of a calibration method according to a first embodiment of the present invention, as shown in fig. 1, the method includes:
step 101: and acquiring observed quantity data of the inertial navigation device.
In some optional embodiments, the obtaining observed quantity data of the inertial navigation device includes:
and acquiring observed quantity data acquired by preset hardware.
The preset hardware can be a gyroscope, an acceleration sensor and other devices capable of collecting observed quantities.
It should be noted that the observed quantity may include various parameters, such as angular velocity, acceleration, and the like. Each observation comprises X, Y, Z observations on the 3 axes.
For example, the observation data may be observation data of angular velocity or observation data of acceleration.
Note that, in the present embodiment, the kind of the observed quantity is not limited. For example, the observation data includes only angular velocity observation data; for another example, the observed quantity data only includes acceleration observed data; as another example, the observation amount data includes angular velocity observation data and acceleration observation data.
Step 102: and obtaining the observed quantity difference value between the current time and the last time based on the observed quantity data.
In some optional embodiments, the obtaining a difference value between the observed quantity of the current time and the observed quantity of the last time based on the observed quantity data includes:
and determining the difference value of the observed quantity of the current time and the observed quantity of the last time based on the observed quantity data of the current time and the observed quantity data of the last time.
Here, the observed quantity data of this time and the observed quantity data of the last time are both the original observed quantity data acquired through the preset hardware acquired through step 101.
Here, the observed quantity data of this time may be understood as the current time tiCollected observation data; the last observed quantity data can be understood as the last time ti-1Collected observation data.
Step 103: and comparing the difference value of the observed quantity with a preset difference parameter threshold.
In some optional embodiments, before comparing the observed quantity difference value with a preset difference parameter threshold, the method further includes:
determining the acquisition time corresponding to the observed quantity data;
determining a time period of the acquisition time;
and determining a preset difference parameter threshold matched with the time period based on the time period.
That is, the preset difference parameter thresholds corresponding to different time periods are different.
For different types of observed quantities, corresponding preset difference parameter thresholds are different; for the same observed quantity, the corresponding preset difference parameter thresholds on X, Y, Z axes are also different.
To facilitate improving the accuracy of the correction, in some optional embodiments, the method further comprises:
counting the variance value of the observed quantity at intervals of a certain time;
determining a preset difference parameter threshold based on the observed quantity variance value;
and the preset difference parameter thresholds of the same observed quantity on different axes are different.
Here, the certain time may be obtained by statistics of a large amount of data, or may be set or adjusted according to a requirement for correction accuracy. For example, the interval time is long under the condition of stable data; in the case of unstable data, the interval time is short.
Therefore, the preset difference parameter threshold is determined periodically, and the preset difference parameter threshold is updated and adjusted in time, so that a more accurate comparison result is obtained conveniently, and the observed quantity data of this time can be corrected according to the comparison result.
Step 104: and correcting the observed quantity data of this time according to the comparison result.
In some optional embodiments, the correcting the observed quantity data according to the comparison result includes:
when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy;
and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
Therefore, the correction strategy is determined according to the comparison result, and the observed quantity data of the current time is corrected according to the determined correction strategy, so that the unstable data can be removed.
Specifically, the first correction strategy includes:
determining a weight value of the observation quantity of this time and a weight value of the observation quantity of the last time obtained after correction;
and taking the combination value of the observed quantity of the current time and the observed quantity of the last time obtained after correction under a certain weight as a correction result for correcting the observed quantity data of the current time.
Specifically, a small weight is given to the value at the current time, and a large weight is given to the last value. The method has the advantages that on one hand, the jitter of zero-offset observed quantity is reduced, and on the other hand, when the observed quantity of the inertial navigation device slowly drifts, the synchronous follow-up can be carried out in real time.
For example, MeaValueLast represents the last observed quantity obtained after correction, meavalueenow represents the current observed quantity, α represents the weight value of the last observed quantity obtained after correction, β represents the weight value of the current observed quantity, and specifically, the correction result obtained by correcting the current observed quantity data is α MeaValueLast + β meavalueenow, for example, α is 0.99, and β is 0.01.
That is, each obtained observed quantity of this time is transmitted to the next calculation, and becomes the next observed quantity of the last time.
Specifically, the second correction policy includes:
and taking the last observation obtained through correction as a correction result for correcting the observation data of this time.
Specifically, if the current observed quantity has too large jitter, the last observed quantity is still assigned to the current observed quantity for the next iteration.
For example, MeaValueLast indicates the previous observed quantity obtained by correction, and specifically, the result of correction of the observed quantity data of this time is MeaValueLast.
The correction method of the embodiment can remove unstable data from original observed quantity data, and endows different weight values according to different shaking conditions of the observed quantity so as to ensure the stability of the corrected observed quantity data and finally output stable observed quantity data.
The correction method of the embodiment can be applied to the field of zero offset error correction of inertial navigation devices.
The existing Kalman filtering method is too complex, the resource consumption of the system is large, and the Kalman filtering method uses the precondition that the system is stable along with time, and the observed quantity of the inertial navigation device obviously does not meet the requirement. In addition, an error covariance matrix must be solved in Kalman filtering to establish an accurate model, otherwise, the filter is difficult to converge. The correction method of the embodiment is a simple sliding filter, but obviously avoids the defects of a plurality of Kalman filters, is simple and easy to realize, and has good effect after actual test.
By adopting the technical scheme of the embodiment of the invention, the observed quantity data of the inertial navigation device is obtained; obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data; comparing the difference value of the observed quantity with a preset difference parameter threshold; and correcting the observed quantity data of this time according to the comparison result. Therefore, a new zero offset correction method is provided, and the problem of accumulated error caused by the fact that the fixed zero offset does not change along with the time can be avoided; and the operation amount is small, the real-time performance is good, and the scheme is simple and easy to realize.
Example two
The embodiment of the invention provides a correction method. Fig. 2 is a schematic flow chart of a calibration method according to a second embodiment of the present invention, as shown in fig. 2, the method includes:
step 201: acquiring original observed quantity data of an inertial navigation device;
step 202: judging whether the acquisition time of the original observed quantity data is in a first time period, if so, executing step 210; if not, go to step 203;
here, the first period of time is 0 to T1; for example, T1 is 60 seconds.
In this embodiment, it is considered that the data jitter in the first time zone is too large, and the observed quantity data in the first time zone is not smoothed.
Step 203: counting the variance of each axis at intervals of a preset frequency, and then executing a step 204;
as the quantization bit and the quantization range of each axis of the inertial navigation device are different, the jitter values are naturally different. In the embodiment, the variance var of each axis is counted at a certain frequency interval, so that a basis is conveniently provided for subsequently setting the difference parameter threshold.
Step 204: judging whether the acquisition time of the original observed quantity data is in a second time period, if so, executing step 205; if not, go to step 206;
here, the second period is T1 to T2; for example, T1 ═ 60 seconds, T2 ═ 180 seconds.
Step 205: determining that the difference parameter threshold adopts a first difference parameter threshold, and then executing step 207;
specifically, if diff _ value represents the difference parameter threshold and var represents the variance, the first difference parameter threshold diff _ value ═ sqrt (var) × γ.
For example, when γ is 10, diff _ value is sqrt (var) 10.
Step 206: determining that the difference parameter threshold adopts a second difference parameter threshold, and then executing step 207;
specifically, if diff _ value represents the difference parameter threshold and var represents the variance, the second difference parameter threshold diff _ value ═ sqrt (var) × δ; wherein δ is less than γ.
For example, when δ is 2, diff _ value ═ sqrt (var) 2.
For example, different difference parameter thresholds are used before and after 180 seconds, the jitter of the first 180 seconds is large, the threshold value is set to sqrt (var) 10, the value is stable after 180 seconds, and the threshold value is set to sqrt (var) 2.
Step 207: judging whether the difference value of the observed quantity data of the current time and the observed quantity data of the last time is less than or equal to the corresponding difference parameter threshold, if so, executing a step 208; if not, go to step 209;
that is, the present-time observed quantity — the last observed quantity < ═ diff _ value is determined.
Step 208: correcting the observed quantity data of this time by adopting a first correction strategy;
specifically, the first correction strategy includes:
the result of correction of this observed quantity data is α, the last observed quantity obtained after correction is + β, α represents the weight value of the last observed quantity obtained after correction, and β represents the weight value of the observed quantity.
For example, when α is 0.99 and β is 0.01, the result of correction of the current observed quantity data is 0.99, and the current observed quantity is + 0.01.
That is, if the difference between the two observed quantities is within the threshold range, the current observed and measured value calculated each time is the combined value of the last observed quantity and the current observed quantity under a certain weight.
Step 209: correcting the observed quantity data of this time by adopting a second correction strategy;
specifically, the second correction policy includes:
the result of correction of the observation data of this time is the last observation obtained after correction.
That is, if the two observations are outside the threshold range, which indicates that the current observation has too much jitter, the last observation is still assigned to the current observation for the next iteration.
In normal jitter, each measurement value should be within the range of diff _ value, so the zero offset correction method of this embodiment is equivalent to a sliding weighting filter, and a small weight is given to the value at the current moment, and a large weight is given to the last value. The method has the advantages that on one hand, the jitter of zero-offset observed quantity is reduced, and on the other hand, when the observed quantity of the inertial navigation device slowly drifts, the synchronous follow-up can be carried out in real time.
Step 210: and outputting the observation quantity data obtained after correction processing.
In this way, stable observation amount data can be obtained.
According to the technical scheme, observation quantity variances of all axes are counted at intervals of a certain frequency, so that influences of temperature drift and the like on the inertial navigation device are eliminated; using different parameters in different time intervals helps to shave out unstable data; according to different shaking conditions of the observed quantity, different weight values are given, each observed quantity comprises the observed quantity corrected last time, and the corrected observed quantity can be more convergent.
EXAMPLE III
The embodiment of the invention also provides a correcting device, and fig. 3 is a schematic structural diagram of a composition of the correcting device of the embodiment of the invention; as shown in fig. 3, the correction device includes: an acquisition unit 31, a determination unit 32, a comparison unit 33, and a correction unit 34; wherein the content of the first and second substances,
the acquiring unit 31 is configured to acquire observed quantity data of an inertial navigation device;
the determining unit 32 is configured to obtain an observed quantity difference value between this time and the last time based on the observed quantity data;
the comparing unit 33 is configured to compare the observed component difference value with a preset difference parameter threshold;
and the correcting unit 34 is configured to correct the observation quantity data of this time according to the comparison result.
Further optionally, the apparatus further comprises:
a statistical unit 35 configured to count an observed quantity variance value at a certain frequency interval;
a setting unit 36, configured to determine a preset difference parameter threshold based on the observed quantity variance value;
and the preset difference parameter thresholds of the same observed quantity on different axes are different.
In some optional embodiments, the comparing unit 33 is further configured to:
determining the acquisition time corresponding to the observed quantity data;
determining a time period of the acquisition time;
and determining a preset difference parameter threshold matched with the time period based on the time period.
In some optional embodiments, the correction unit 34 is further configured to:
when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy;
and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
Optionally, the first correction strategy includes:
determining a weight value of the observation quantity of this time and a weight value of the observation quantity of the last time obtained after correction;
and taking the combination value of the observed quantity of the current time and the observed quantity of the last time obtained after correction under a certain weight as a correction result for correcting the observed quantity data of the current time.
Optionally, the second correction policy includes:
and taking the last observation obtained through correction as a correction result for correcting the observation data of this time.
It should be noted that: in practice, the above-mentioned processing distribution may be completed by different program modules according to needs, that is, the internal structure of the server is divided into different program modules to complete all or part of the above-mentioned processing. In addition, the calibration device and the calibration method provided by the above embodiments belong to the same concept, and specific implementation processes thereof are described in the method embodiments and are not described herein again.
In the embodiment of the present invention, the obtaining Unit 31, the determining Unit 32, the comparing Unit 33, the correcting Unit 34, the counting Unit 35, and the setting Unit 36 in the correcting device may be implemented by a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a Micro Control Unit (MCU), or a Programmable Gate Array (FPGA) in an inertial navigation device where the correcting device is located in an actual application.
The correcting device of the embodiment of the invention provides a new zero offset correcting scheme, which can not only avoid the problem of accumulated errors caused by the fact that the fixed zero offset does not change along with the time; and the operation amount is small, the real-time performance is good, and the scheme is simple and easy to realize.
Example four
The embodiment of the invention also provides a correction device. Fig. 4 is a schematic diagram of a hardware structure of the calibration apparatus according to the embodiment of the present invention, and as shown in fig. 4, the calibration apparatus includes: at least one processor 41, a memory 42 and a computer program stored on the memory 42 and executable on the processor 41, the correction device further comprising a communication interface 43; the various components of the correction device are coupled together by a bus system 44. It will be appreciated that the bus system 44 is used to enable communications among the components. The bus system 44 includes a power bus, a control bus, and a status signal bus in addition to the data bus. For clarity of illustration, however, the various buses are labeled as bus system 44 in fig. 4.
It will be appreciated that the memory 42 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 42 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The method disclosed in the above embodiments of the present invention may be applied to the processor 41, or implemented by the processor 41. The processor 41 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 41. The processor 41 described above may be a general purpose processor, a DSP, or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 41 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in memory 42, where processor 41 reads the information in memory 42 and in combination with its hardware performs the steps of the method described above.
In an exemplary embodiment, the calibration Device may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), FPGAs, general purpose processors, controllers, MCUs, microprocessors (microprocessors), or other electronic components for performing the aforementioned methods.
In this embodiment, when the processor 41 executes the program, it implements: acquiring observed quantity data of an inertial navigation device; obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data; comparing the difference value of the observed quantity with a preset difference parameter threshold; and correcting the observed quantity data of this time according to the comparison result.
As an embodiment, the processor 41, when executing the program, implements: counting the variance value of the observed quantity at intervals of a certain frequency; determining a preset difference parameter threshold based on the observed quantity variance value; and the preset difference parameter thresholds of the same observed quantity on different axes are different.
As an embodiment, the processor 41, when executing the program, implements: before comparing the observed quantity difference value with a preset difference parameter threshold, determining the acquisition time corresponding to the observed quantity data of this time; determining a time period of the acquisition time; and determining a preset difference parameter threshold matched with the time period based on the time period.
As an embodiment, the processor 41, when executing the program, implements: when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy; and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
EXAMPLE five
Embodiments of the present invention also provide a computer storage medium, such as the memory 42 shown in fig. 4, comprising a computer program, which is executable by the processor 41 of the server to perform the steps of the aforementioned method. The computer storage medium can be FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface Memory, optical disk, or CD-ROM; or may be various devices including one or any combination of the above memories.
The computer storage medium provided by the embodiment of the invention is stored with computer instructions, and the instructions are executed by a processor to realize that: acquiring observed quantity data of an inertial navigation device; obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data; comparing the difference value of the observed quantity with a preset difference parameter threshold; and correcting the observed quantity data of this time according to the comparison result.
As an embodiment, the instructions when executed by the processor implement: counting the variance value of the observed quantity at intervals of a certain frequency; determining a preset difference parameter threshold based on the observed quantity variance value; and the preset difference parameter thresholds of the same observed quantity on different axes are different.
As an embodiment, the instructions when executed by the processor implement: before comparing the observed quantity difference value with a preset difference parameter threshold, determining the acquisition time corresponding to the observed quantity data of this time; determining a time period of the acquisition time; and determining a preset difference parameter threshold matched with the time period based on the time period.
As an embodiment, the instructions when executed by the processor implement: when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy; and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
In the several embodiments provided in the present application, it should be understood that the disclosed server and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method of calibration, the method comprising:
acquiring observed quantity data of an inertial navigation device;
obtaining an observed quantity difference value between the current time and the last time based on the observed quantity data;
comparing the difference value of the observed quantity with a preset difference parameter threshold;
and correcting the observed quantity data of this time according to the comparison result.
2. The method of claim 1, further comprising:
counting the variance value of the observed quantity at intervals of a certain time;
determining a preset difference parameter threshold based on the observed quantity variance value;
and the preset difference parameter thresholds of the same observed quantity on different axes are different.
3. The method of claim 1, wherein comparing the observed component difference value to a predetermined difference parameter threshold further comprises:
determining the acquisition time corresponding to the observed quantity data;
determining a time period of the acquisition time;
and determining a preset difference parameter threshold matched with the time period based on the time period.
4. The method according to claim 3, wherein the correcting the observed quantity data of the time according to the comparison result comprises:
when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy;
and when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy.
5. The method of claim 4,
the first correction strategy comprising:
determining a weight value of the observation quantity of this time and a weight value of the observation quantity of the last time obtained after correction;
taking the combination value of the observed quantity of the current time and the observed quantity of the last time obtained after correction under a certain weight as a correction result for correcting the observed quantity data of the current time;
the second correction policy comprising:
and taking the last observation obtained through correction as a correction result for correcting the observation data of this time.
6. A calibration device, characterized in that the calibration device comprises: the device comprises an acquisition unit, a determination unit, a comparison unit and a correction unit; wherein the content of the first and second substances,
the acquisition unit is used for acquiring observed quantity data of the inertial navigation device;
the determining unit is used for obtaining the observed quantity difference value between the current time and the last time based on the observed quantity data;
the comparison unit is used for comparing the observed component difference value with a preset difference parameter threshold;
and the correction unit is used for correcting the observation quantity data of this time according to the comparison result.
7. The apparatus of claim 6, further comprising:
the statistical unit is used for counting the variance value of the observed quantity at intervals of a certain time;
the setting unit is used for determining a preset difference parameter threshold based on the observed quantity variance value;
and the preset difference parameter thresholds of the same observed quantity on different axes are different.
8. The apparatus according to claim 6, wherein the comparing unit is further configured to determine, before comparing the observed quantity difference value with a preset difference parameter threshold, an acquisition time corresponding to the observed quantity data of this time; determining a time period of the acquisition time; and determining a preset difference parameter threshold matched with the time period based on the time period.
9. The apparatus of claim 8, wherein the correction unit is further configured to:
when the observed quantity difference value is smaller than or equal to a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a first correction strategy;
when the observed quantity difference value is larger than a preset difference parameter threshold, correcting the observed quantity data of this time by adopting a second correction strategy;
wherein the first correction strategy comprises:
determining a weight value of the observation quantity of this time and a weight value of the observation quantity of the last time obtained after correction;
taking the combination value of the observed quantity of the current time and the observed quantity of the last time obtained after correction under a certain weight as a correction result for correcting the observed quantity data of the current time;
wherein the second correction policy comprises:
and taking the last observation obtained through correction as a correction result for correcting the observation data of this time.
10. A computer storage medium having computer instructions stored thereon, wherein the instructions, when executed by a processor, implement the steps of the correction method of any one of claims 1 to 5.
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|---|---|---|---|---|
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Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010080383A1 (en) * | 2009-01-07 | 2010-07-15 | Sensor Platforms, Inc | System and method for determining an attitude of a device undergoing dynamic acceleration using a kalman filter |
| CN102508278A (en) * | 2011-11-28 | 2012-06-20 | 北京航空航天大学 | Adaptive filtering method based on observation noise covariance matrix estimation |
| CN102506857A (en) * | 2011-11-28 | 2012-06-20 | 北京航空航天大学 | Relative attitude measurement real-time dynamic filter method based on dual-inertial measurement unit/differential global positioning system (IMU/DGPS) combination |
| CN104122412A (en) * | 2014-07-29 | 2014-10-29 | 北京机械设备研究所 | Accelerometer calibrating method based on Beidou second generation velocity information |
| CN104297772A (en) * | 2013-07-16 | 2015-01-21 | 成都国星通信有限公司 | Carrier phase differential-based dual-antenna integrated positioning and orientation system and method |
| CN104880201A (en) * | 2015-03-26 | 2015-09-02 | 武汉大学 | Automatic calibration method of MEMS gyroscopes |
| CN105792135A (en) * | 2014-12-23 | 2016-07-20 | 中国移动通信集团公司 | Method and device for positioning lane where vehicle is |
| CN106324645A (en) * | 2016-08-19 | 2017-01-11 | 付寅飞 | Vehicle accuracy positioning method based on inertial navigation and satellite differential positioning |
| CN106646570A (en) * | 2017-01-12 | 2017-05-10 | 付寅飞 | Multi-base-station satellite differential positioning and inertia combination vehicle precise positioning method |
| CN107515011A (en) * | 2017-07-07 | 2017-12-26 | 青岛海信移动通信技术股份有限公司 | A kind of bearing calibration of gyroscope and device |
| CN107764257A (en) * | 2017-09-14 | 2018-03-06 | 中国电子科技集团公司第五十四研究所 | A kind of inertia device method for numerical simulation |
| CN108287354A (en) * | 2017-01-09 | 2018-07-17 | 北京四维图新科技股份有限公司 | A kind of data automatic error correction method and device and navigation equipment |
| CN108519105A (en) * | 2018-03-09 | 2018-09-11 | 天津大学 | A kind of zero-speed correction localization method based on difference statistics |
-
2018
- 2018-11-14 CN CN201811355307.8A patent/CN111189471A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010080383A1 (en) * | 2009-01-07 | 2010-07-15 | Sensor Platforms, Inc | System and method for determining an attitude of a device undergoing dynamic acceleration using a kalman filter |
| CN102508278A (en) * | 2011-11-28 | 2012-06-20 | 北京航空航天大学 | Adaptive filtering method based on observation noise covariance matrix estimation |
| CN102506857A (en) * | 2011-11-28 | 2012-06-20 | 北京航空航天大学 | Relative attitude measurement real-time dynamic filter method based on dual-inertial measurement unit/differential global positioning system (IMU/DGPS) combination |
| CN104297772A (en) * | 2013-07-16 | 2015-01-21 | 成都国星通信有限公司 | Carrier phase differential-based dual-antenna integrated positioning and orientation system and method |
| CN104122412A (en) * | 2014-07-29 | 2014-10-29 | 北京机械设备研究所 | Accelerometer calibrating method based on Beidou second generation velocity information |
| CN105792135A (en) * | 2014-12-23 | 2016-07-20 | 中国移动通信集团公司 | Method and device for positioning lane where vehicle is |
| CN104880201A (en) * | 2015-03-26 | 2015-09-02 | 武汉大学 | Automatic calibration method of MEMS gyroscopes |
| CN106324645A (en) * | 2016-08-19 | 2017-01-11 | 付寅飞 | Vehicle accuracy positioning method based on inertial navigation and satellite differential positioning |
| CN108287354A (en) * | 2017-01-09 | 2018-07-17 | 北京四维图新科技股份有限公司 | A kind of data automatic error correction method and device and navigation equipment |
| CN106646570A (en) * | 2017-01-12 | 2017-05-10 | 付寅飞 | Multi-base-station satellite differential positioning and inertia combination vehicle precise positioning method |
| CN107515011A (en) * | 2017-07-07 | 2017-12-26 | 青岛海信移动通信技术股份有限公司 | A kind of bearing calibration of gyroscope and device |
| CN107764257A (en) * | 2017-09-14 | 2018-03-06 | 中国电子科技集团公司第五十四研究所 | A kind of inertia device method for numerical simulation |
| CN108519105A (en) * | 2018-03-09 | 2018-09-11 | 天津大学 | A kind of zero-speed correction localization method based on difference statistics |
Non-Patent Citations (2)
| Title |
|---|
| 张秋昭等编著: "《GPS辅助SINS动态对准关键模型研究》", 30 April 2016 * |
| 王革超等: "加速度差分有限状态机计布算法", 《计算机科学与探索》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112001570A (en) * | 2020-09-29 | 2020-11-27 | 北京嘀嘀无限科技发展有限公司 | Data processing method and device, electronic equipment and readable storage medium |
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