CN116380148B - Two-stage space-time error calibration method and device for multi-sensor target tracking system - Google Patents
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Abstract
The invention discloses a two-stage space-time error calibration method and device for a multi-sensor target tracking system, and belongs to the technical field of target detection and tracking. The method comprises the following steps: calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; performing first error correction on the sensing source to be calibrated based on the time error compensation amount and the position error compensation amount; calculating a second-stage system error subjected to the first error correction; and carrying out second error correction on the to-be-calibrated sensing source based on the second-stage system error. The invention can solve the problem that the track cannot be associated due to large system deviation or the track association threshold is set too large to cause error association so as to introduce calculation errors, effectively reduces the range of the system errors among the sensors and improves the error correction precision.
Description
Technical Field
The invention belongs to the technical field of target detection tracking, in particular relates to a multi-sensor target tracking system, and particularly relates to a two-stage space-time error calibration method and device of the multi-sensor target tracking system.
Background
The multi-sensor networking system can realize information complementation by utilizing a data fusion technology (for example, carrying out data fusion on a radar and an infrared sensor), improve the target tracking precision and the recognition capability, and enhance the anti-interference performance of the target tracking system.
However, in practice, due to factors such as sensor performance difference, data processing mode difference, dynamic change of networking environment and the like, the target tracks output by the sensor system are easy to generate system deviation of different degrees, so that difficulty of data association and data fusion is increased, performance indexes are obviously reduced after the target data fusion, and the advantage of the sensor system for cooperative networking is lost, so that the elimination of space-time errors among the sensor systems becomes a key basis for improving the cooperative efficiency.
At present, calibration is usually performed by adopting different cooperative source references in a sensor system, including civil aviation ADS-B, satellite calibration or a sensor source with higher measurement precision in a networking system, and the calibration flow usually comprises time registration, track association, error estimation and the like. Time registration refers to the time alignment of sensors of different data rates to obtain data points of the same time; the track association and the error estimation have a mutual coupling relation, on one hand, the corresponding relation between the calibration source and the detection result of the sensor is obtained through the track association, so that the error is estimated, and on the other hand, the error estimation influences the association threshold design, so that the error association degree is determined. In practical application, error interference such as time delay between a sensor to be calibrated and a calibration source can cause mutual association failure of the same measurement, and influence error estimation results, so that data fusion accuracy is seriously reduced.
Disclosure of Invention
The invention aims to disclose a two-stage space-time error calibration method and a device for a multi-sensor target tracking system, so as to improve the data fusion precision of the multi-sensor target tracking system.
In the 1 st aspect of the invention, a two-stage space-time error calibration method of a multi-sensor target tracking system is provided, and the method comprises the following steps:
calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
performing first error correction on the sensing source to be calibrated based on the time error compensation amount and the position error compensation amount;
calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
and carrying out second error correction on the to-be-calibrated sensing source based on the second-stage system error.
In other embodiments, the calculating the time error compensation amount and the position error compensation amount for compensating the first stage system error includes:
acquiring two-dimensional images of a sensing source and a reference source to be calibrated under the same coordinate system;
extracting a key point group of which the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source are matched with each other;
solving parameters of a coordinate mapping matrix between the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source based on the key point group;
the time error compensation amount and the position error compensation amount are calculated based on the parameters of the coordinate mapping matrix and the parameters of the two-dimensional image.
In other embodiments, the two-dimensional image comprises a time-azimuth two-dimensional image, a time-elevation two-dimensional image, and a time-pitch two-dimensional image, and the position error compensation amount comprises an azimuth error compensation amount, an elevation error compensation amount, and a pitch error compensation amount.
In other embodiments, the parameters of the coordinate mapping matrix between the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source are solved by using a least square method based on the key point group, and the parameters comprise a rotation factor and a translation factor.
Wherein the time error compensation amount is calculated based on a first translation factor of the coordinate mapping matrix, an abscissa range of the two-dimensional image, and a corresponding time range.
Wherein the position error compensation amount is calculated based on a second translation factor of the coordinate mapping matrix, an abscissa range and a position range of the two-dimensional image; the position range includes an azimuth range, a pitch range, and a pitch range.
In another embodiment, the calculating the second level system error after the first error correction includes:
a time registration step, namely taking a data source time point with lower data rate in the sensing source to be calibrated and the reference source as a reference time point, and interpolating from a data source with high data rate to the reference time point;
a track association step, namely generating a plurality of target association groups between the sensing source to be calibrated and the reference source based on a set association threshold;
and in the error estimation step, calculating the average value of the cost matrix values corresponding to each target association group to obtain the second-stage system error.
In other embodiments, m target tracks of the sensing source to be calibrated and l target tracks of the reference source form an m×l dimension cost matrix on azimuth, pitch and slant distances respectively, the cost matrix values are elements of each cost matrix, the azimuth error, the pitch error and the slant distance error between the sensing source to be calibrated and the target combination of the reference source are respectively represented, and when the azimuth error, the pitch error and the slant distance error of a certain target combination are respectively lower than respective association thresholds, the certain target combination is taken as a target association group.
In the 2 nd aspect of the present invention, there is provided a two-stage space-time error calibration device for a multi-sensor target tracking system, the device comprising:
the first calculation module is used for calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
the first correction module is used for carrying out first error correction on the sensing source to be calibrated based on the time error compensation quantity and the position error compensation quantity;
the second calculation module is used for calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
and the second correction module is used for carrying out second error correction on the sensing source to be calibrated based on the second-stage system error.
In a 3 rd aspect of the present invention, there is provided a two-stage spatio-temporal error calibration apparatus of a multi-sensor target tracking system, comprising a memory unit storing a computer program which, when executed by a processor, performs the operations of:
calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
performing first error correction on the sensing source to be calibrated based on the time error compensation amount and the position error compensation amount;
calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
and carrying out second error correction on the to-be-calibrated sensing source based on the second-stage system error.
Compared with the prior art, the method can decouple the relativity between the track association and the error estimation step by carrying out the error grading treatment, and solves the problems that the track cannot be associated due to large system deviation or the track association threshold is excessively set to cause error association so as to introduce calculation errors.
In addition, the sensitivity of people to high-dimensional data processing is fully utilized, the problem of large system errors of the sensing source is solved through the thought of image key feature extraction and key point matching, the large system errors are displayed more intuitively, the range of the system errors among the sensors is effectively reduced, and the error correction precision is improved.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of a two-stage spatio-temporal error calibration method of a multi-sensor target tracking system according to an embodiment of the present invention;
FIG. 2 is an example of reference source and calibrated sensor source image generation (exemplified by a time-azimuth image);
FIG. 3 is an example of reference source and sensor source image feature extraction with calibration;
FIG. 4 is a keypoint match example;
FIG. 5 is an example of the azimuth angle of the original data after the first error correction;
fig. 6 is an example of azimuth angle of the original data after two-stage error correction.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
The method processes the error of the multi-sensor target tracking system in a layered manner by considering the coupling of track association and error estimation, and reduces the error range after processing alone when the track association is unsuccessful and the error estimation is not performed for large measurement errors (hereinafter referred to as first-stage system errors) caused by factors such as large time delay. After the first-stage error correction or compensation process, a second-stage system error (including measurement errors caused by sensor performance differences and the like) is obtained through track association and error estimation. That is, the invention divides the system error difference between the sensors into two stages according to different error sources, wherein the first stage system error is a larger system error formed by factors such as large time delay, and the second stage system error is a system error formed by the sensors during measurement due to performance difference.
FIG. 1 is a flow chart of a two-stage space-time error calibration method of a multi-sensor target tracking system according to an embodiment of the invention. As shown in fig. 1, the method includes:
step 100, calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error;
for the first-stage system error, because the error is larger, different sensing measurements of the same target can be correlated only by setting a larger correlation threshold, more error correlation can be introduced into the larger correlation threshold to form a plurality of error correlation groups, and error of error correlation can be introduced into the real system error in subsequent error estimation, so that the first-stage system error cannot be directly obtained by carrying out error estimation after track correlation.
According to an embodiment of the present invention, the specific calculation process of this step includes:
step 101, acquiring two-dimensional images of a sensing source and a reference source to be calibrated under the same coordinate system;
converting the detection result of the sensing source to be calibrated into the northeast day coordinate system of the calibration reference source through coordinate transformation to respectively obtain two-dimensional images such as time-azimuth, time-pitching, time-oblique distance and the like of the sensing source to be calibrated and the calibration reference source, wherein the abscissa range of each two-dimensional image is [0, x ] lim ]The corresponding time range is [ t ] start ,t end ]The ordinate range of the image is [0, y lim ]The corresponding azimuth/pitch/skew range is [ v 1 ,v 2 ]。
102, extracting a key point group of which the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source are mutually matched;
respectively extracting a sensing source to be calibrated and a targetAnd correcting the key point characteristics of the reference source in the two-dimensional images of time-azimuth, time-pitching and time-oblique distance to obtain the key characteristics of matching the two images. By matching key features, mutually matched key point groups can be obtained. Here, note that the image 1 matches the keypoint coordinates as: [ X ] i ,Y i ]Where i=1, 2, …, n, the keypoint coordinates in image 2 matching image 1 are: [ X ] j ,Y j ]Where j=1, 2, …, n.
As an example, image feature point descriptors may be generated based on SURF or SIFT algorithms to extract a set of keypoints where the two-dimensional image of the sensing source to be calibrated matches the two-dimensional image of the reference source.
Step 103, solving parameters of a coordinate mapping matrix between the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source based on the key point group;
the mapping relation between the two image coordinates is as follows:
wherein, the coordinate mapping matrix H is:
wherein a is 11 ,a 12 ,a 21 ,a 22 Representing twiddle factor, a 13 ,a 23 The translation factor is represented, and the translation amounts of the X axis and the Y axis are respectively represented.
By inputting a plurality of groups of matching key point coordinates, 6 unknown parameters a in the mapping matrix can be obtained by a least square method 11 ,a 12 ,a 21 ,a 22 ,a 13 ,a 23 。
Step 104, calculating the time error compensation amount and the position error compensation amount based on the parameters of the coordinate mapping matrix and the parameters of the two-dimensional image.
Specifically, the time error compensation amount in the first-stage system error can be calculated by the following formula:
the error compensation amounts of azimuth, pitch and pitch in the first-stage system error can be calculated by the following formulas respectively:
and 200, carrying out first error correction on the sensing source to be calibrated based on the time error compensation amount and the position error compensation amount.
Step 300, calculating a second-stage system error after the first error correction;
the second-stage systematic error is the residual error after the 1 st-stage error processing, and the stage systematic error is relatively small, so that the second-stage systematic error can be obtained by a time registration-track correlation-error estimation flow, and the specific steps are as follows:
step 301, a time registration step;
and taking a data source time point with lower data rate in the sensing source to be calibrated and the reference source as a reference time point, and interpolating the reference time point by a data source with high data rate. Specifically, a data source time point with lower data rate in a sensing source to be calibrated and a calibration reference source is selected as a reference value (reference time point), interpolation is carried out from a data source with high data rate to the reference time point, so that accurate and smooth interpolation data can be ensured, and the coordinates of the reference value of the azimuth, the pitch and the skew of the low data rate data source are recorded as follows: (t) i ,A i ),(t i ,E i ),(t i ,R i ) Wherein i=1, 2, …, n, the coordinates of the corresponding times after interpolation of the high data rate data sources are respectively: (t) i ,A i '),(t i ,E i '),(t i ,R i '), where i=1, 2, …, n.
302, a track association step;
and generating a plurality of target association groups between the sensing source to be calibrated and the reference source based on the set association threshold.
In other embodiments, m target tracks of the sensing source to be calibrated and l target tracks of the reference source form an m×l dimension cost matrix on azimuth, pitch and slant distances respectively, the cost matrix values are elements of each cost matrix, the azimuth error, the pitch error and the slant distance error between the sensing source to be calibrated and the target combination of the reference source are respectively represented, and when the azimuth error, the pitch error and the slant distance error of a certain target combination are respectively lower than respective association thresholds, the certain target combination is taken as a target association group.
Specifically, the association thresholds of azimuth, pitching and pitch are set as d respectively 1 ,d 2 ,d 3 . In the period of calibration, m target tracks exist in a sensing source to be calibrated, and l targets exist in a reference source to be calibrated, so that an m multiplied by l dimension cost matrix is formed on the azimuth, the pitching and the inclined distance respectively:
wherein the elements of the cost matrixRepresenting the error between two data source target combinations, p=1, …, l, q=1, …, m, when V is a, E, R, V 'is a', E ', R', c, respectively pq ≤d 1 ,c pq ≤d 2 ,c pq ≤d 3 And when the target is satisfied, the q-th target of the sensing source to be calibrated is considered to be associated with the p-th target of the calibration reference source, so that a plurality of association groups are formed.
Step 303, an error estimation step;
and calculating the average value of the cost matrix values corresponding to each target association group to obtain the second-stage system error. Specifically, the serial number of the association group is used as an index, and a cost matrix value c formed by the association group in azimuth, pitch and inclined distance respectively is taken pq Averaging to obtain azimuth, pitch and pitchSecond order systematic error Deltav 2 。
Referring to fig. 2, taking azimuth (azimuth) as an example, the original image P0 includes a sensor source to be calibrated and calibration reference source data (abscissa is message detection time, and ordinate is azimuth), and a reference source two-dimensional image P11 and a sensor source two-dimensional image P21 to be calibrated are obtained based on the original image P0. Fig. 3 shows that the reference source two-dimensional image P11 and the sensor source two-dimensional image P21 to be calibrated are respectively subjected to feature extraction to obtain key features P12 and P22 matched with the two images. Fig. 4 is a set of keypoints that are matched to each other by matching key features.
Fig. 5 and fig. 6 are schematic diagrams of the results of the first error correction and the second error correction of the original image data, respectively. According to the invention, through the extraction of the key features of the image, the problem of large system errors of the sensing sources can be solved by key point matching, so that the large system errors are displayed more intuitively, the range of the system errors among the sensors is effectively reduced, and the error correction precision is improved. Meanwhile, the method can decouple the relativity between the track association and the error estimation step by carrying out the error grading treatment, and solve the problem that the track cannot be associated due to large system deviation or the track association threshold is excessively set to cause error association so as to introduce calculation errors.
According to a further aspect of the present invention, there is also provided a two-stage spatio-temporal error calibration apparatus of a multi-sensor target tracking system, the apparatus comprising:
the first calculation module is used for calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
the first correction module is used for carrying out first error correction on the sensing source to be calibrated based on the time error compensation quantity and the position error compensation quantity;
the second calculation module is used for calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
and the second correction module is used for carrying out second error correction on the sensing source to be calibrated based on the second-stage system error.
According to a further aspect of the present invention there is also provided a two-stage spatio-temporal error calibration apparatus for a multi-sensor target tracking system, comprising a memory unit storing a computer program which, when executed by a processor, performs the operations of:
calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
performing first error correction on the sensing source to be calibrated based on the time error compensation amount and the position error compensation amount;
calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
and carrying out second error correction on the to-be-calibrated sensing source based on the second-stage system error.
In the present invention, the processor may be a central processing unit (Central Processing Unit, CPU), or other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or a combination thereof. The storage unit may be a transient memory or a non-transient memory.
Although the present invention has been described in more detail by way of the above embodiments, the present invention is not limited to the above embodiments, and modifications and equivalents may be made to the technical solutions of the embodiments of the present invention without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. A two-stage spatio-temporal error calibration method of a multi-sensor target tracking system, the method comprising:
calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
performing first error correction on the sensing source to be calibrated based on the time error compensation amount and the position error compensation amount;
calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
performing second error correction on the sensing source to be calibrated based on the second-stage system error;
the calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error includes:
acquiring two-dimensional images of a sensing source and a reference source to be calibrated under the same coordinate system;
extracting a key point group of which the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source are matched with each other;
solving parameters of a coordinate mapping matrix between the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source based on the key point group;
calculating the time error compensation amount and the position error compensation amount based on the parameters of the coordinate mapping matrix and the parameters of the two-dimensional image;
the calculating the second-stage system error after the first error correction comprises the following steps:
a time registration step, namely taking a data source time point with lower data rate in the sensing source to be calibrated and the reference source as a reference time point, and interpolating from a data source with high data rate to the reference time point;
a track association step, namely generating a plurality of target association groups between the sensing source to be calibrated and the reference source based on a set association threshold;
an error estimation step, namely calculating an average value of cost matrix values corresponding to each target association group to obtain a second-stage system error;
the method comprises the steps that m target tracks of a sensing source to be calibrated and l target tracks of a reference source form an m multiplied by l dimension cost matrix on azimuth, pitching and inclined distances respectively, the cost matrix value is an element of each cost matrix and represents azimuth error, pitching error and inclined distance error between target combinations of the sensing source to be calibrated and the reference source respectively, and when the azimuth error, pitching error and inclined distance error of a certain target combination are respectively lower than respective association thresholds, the certain target combination is taken as a target association group.
2. The two-stage spatio-temporal error correction method according to claim 1, characterized in that said two-dimensional images include a time-azimuth two-dimensional image, a time-pitch two-dimensional image, and said position error compensation amount includes an azimuth error compensation amount, a pitch error compensation amount, and a pitch error compensation amount.
3. The two-stage spatio-temporal error calibration method according to claim 1, characterized in that parameters of a coordinate mapping matrix between the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source are solved by a least square method based on the set of key points, the parameters including a rotation factor and a translation factor.
4. A two-stage spatio-temporal error correction method according to claim 3, characterized in that said amount of temporal error compensation is calculated based on a first translation factor of said coordinate mapping matrix, the abscissa range of said two-dimensional image and the corresponding time range.
5. A two-stage spatio-temporal error correction method according to claim 3, characterized in that said position error compensation amount is calculated based on a second translation factor of said coordinate mapping matrix, an abscissa range and a position range of said two-dimensional image; the position range includes an azimuth range, a pitch range, and a pitch range.
6. A two-stage spatio-temporal error calibration apparatus for a multi-sensor target tracking system, the apparatus comprising:
the first calculation module is used for calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error; wherein, the first-stage system error is a system error formed by large time delay;
the first correction module is used for carrying out first error correction on the sensing source to be calibrated based on the time error compensation quantity and the position error compensation quantity;
the second calculation module is used for calculating a second-stage system error subjected to the first error correction; the second-stage system error is a system error formed by the sensor during measurement due to performance difference;
the second correction module is used for carrying out second error correction on the sensing source to be calibrated based on the second-stage system error;
the calculating a time error compensation amount and a position error compensation amount for compensating the first-stage system error includes:
acquiring two-dimensional images of a sensing source and a reference source to be calibrated under the same coordinate system;
extracting a key point group of which the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source are matched with each other;
solving parameters of a coordinate mapping matrix between the two-dimensional image of the sensing source to be calibrated and the two-dimensional image of the reference source based on the key point group;
calculating the time error compensation amount and the position error compensation amount based on the parameters of the coordinate mapping matrix and the parameters of the two-dimensional image;
the calculating the second-stage system error after the first error correction comprises the following steps:
a time registration step, namely taking a data source time point with lower data rate in the sensing source to be calibrated and the reference source as a reference time point, and interpolating from a data source with high data rate to the reference time point;
a track association step, namely generating a plurality of target association groups between the sensing source to be calibrated and the reference source based on a set association threshold;
an error estimation step, namely calculating an average value of cost matrix values corresponding to each target association group to obtain a second-stage system error;
the method comprises the steps that m target tracks of a sensing source to be calibrated and l target tracks of a reference source form an m multiplied by l dimension cost matrix on azimuth, pitching and inclined distances respectively, the cost matrix value is an element of each cost matrix and represents azimuth error, pitching error and inclined distance error between target combinations of the sensing source to be calibrated and the reference source respectively, and when the azimuth error, pitching error and inclined distance error of a certain target combination are respectively lower than respective association thresholds, the certain target combination is taken as a target association group.
7. A two-stage spatio-temporal error calibration apparatus of a multi-sensor target tracking system, comprising a memory unit storing a computer program, characterized in that the two-stage spatio-temporal error calibration method of a multi-sensor target tracking system according to claim 1 is implemented when said computer program is executed by a processor.
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