CN113743480A - Multi-source data fusion abnormal value identification method based on mutual consistency - Google Patents

Multi-source data fusion abnormal value identification method based on mutual consistency Download PDF

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CN113743480A
CN113743480A CN202110954195.3A CN202110954195A CN113743480A CN 113743480 A CN113743480 A CN 113743480A CN 202110954195 A CN202110954195 A CN 202110954195A CN 113743480 A CN113743480 A CN 113743480A
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inequalities
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杨涛
沈鹏飞
崔乐园
袁莹莹
冯燕
王宁
幸涛
盛宴铭
王轶
苏帅
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Henan Fangda Space Information Technology Co Ltd
CETC 27 Research Institute
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CETC 27 Research Institute
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Abstract

The invention provides a mutual consistency-based multi-source data fusion abnormal value identification method, which is used for solving the technical problems that the conventional abnormal value identification method is high in misjudgment probability and cannot correctly identify continuous multi-point abnormality. The method comprises the following steps: firstly, dividing the data into m different data sources according to different observation devices; secondly, establishing a functional relation between every two data sources in the m data sources; and finally, judging whether the test element in the data source is abnormal according to the functional relation. The method judges the data consistency by judging whether the functional relation between the test element and the test elements of other data sources is in a normal range, is suitable for three or more independent data sources, does not depend on the continuity of single data, and can identify most abnormal values; the method for judging the abnormal value of the isolated single data source has a good supplementary function, is effective to continuous or discontinuous abnormal values, and can reduce the probability of erroneous judgment of abnormal value identification.

Description

Multi-source data fusion abnormal value identification method based on mutual consistency
Technical Field
The invention relates to the field of aerospace measurement and control and target range measurement data processing, in particular to a multisource data fusion abnormal value identification method based on mutual consistency.
Background
Abnormal value identification is an important ring in data processing in aerospace measurement and control and target range measurement systems, and the abnormal value identification is needed before further calculation processing of observation data generated by measurement equipment of each measurement station. The abnormal value refers to an observed value which is seriously deviated from the actual motion track of the macroscopic target, and the abnormal value can be generally identified according to the rule that the observed data continuously changes along with time.
At present, a classical abnormal value identification correction algorithm is used in the fields of aerospace measurement and control and target range measurement, and judgment is generally carried out based on the continuity of local data points, for example, an algorithm based on second-order polynomial fitting, but the conditions of local continuity and overall abnormality exist, so that misjudgment is caused. The algorithm based on the overall judgment has an advantage in judging the abnormal value in the trend. However, the above methods are all based on the characteristics of the single measurement element, and the information between the multi-source data is not fully utilized in the multi-source data fusion processing.
Disclosure of Invention
Aiming at the defects in the background technology, the invention provides a mutual consistency-based multi-source data fusion abnormal value identification method, which can identify the measured data abnormality of which single source data is difficult to identify when the measured data is preprocessed in real time or before trajectory calculation in the future, and solves the technical problems that the existing abnormal value identification method has high misjudgment probability and continuous multi-point abnormality cannot be identified correctly.
The technical scheme of the invention is realized as follows:
a mutual consistency-based multi-source data fusion abnormal value identification method comprises the following steps:
the method comprises the following steps: dividing the data into m data sources according to different observation devices, wherein the m data sources are different, and m is more than or equal to 3;
step two: constructing a functional relation between every two data sources in the m data sources;
step three: and judging whether the test element in the data source is abnormal or not according to the functional relation.
The function relationship between every two data sources in the m data sources is as follows:
Figure BDA0003219788900000011
wherein, CikFor the ith data source DiThe k-th cell of (1),
Figure BDA0003219788900000012
for the j-th data source, i, j is 1,2, …, m, i ≠ j, k is 1,2, …, ni，niFor the ith data source DiNumber of middle measurement elements, njFor the jth data source DjThe number of middle test elements.
The method for judging whether the test element in the data source is abnormal according to the functional relationship comprises the following steps:
s3.1, setting a test element CikIs given a consistency score of S ik0, the total number of consistency judgments Pik＝0；
S3.2 for data Source DiListing the data sources DiAnd the functional relation between all the measured elements and the measured elements of other data sources is as follows:
Figure BDA0003219788900000021
s3.3, judgment
Figure BDA0003219788900000022
Is true, wherein, δikIs a given threshold;
S3.4、Pik＝Pik+ 1; if the inequality is true, then measure element CikAnd
Figure BDA0003219788900000023
all the consistency scores of (1) are added, namely Sik＝Sik+1，Sj1＝Sj1+1,Sj2＝Sj2+1,...,Sjn＝Sjn+ 1; if the inequality is not true, the consistency score is unchanged;
s3.5, traversing the m data sources, traversing different measuring elements in the data sources, and judging
Figure BDA0003219788900000024
Whether the result is true or not;
s3.6 consistency ratio S to the final resultik/PikMaking a judgment if Sik/PikAnd if not less than 50%, judging that the measured element is normal, otherwise, judging that the measured element is abnormal.
When m is 3, the observation devices are respectively a single pulse device, a multi-speed measurement device and a GNSS device, and one single pulse device, three multi-speed measurement devices and one GNSS device are provided;
at time t, the measured element of the single-pulse device is Rt、At、EtThe measurement element of the multi-speed measurement equipment I is
Figure BDA0003219788900000025
The measurement element of the multi-speed measurement equipment II is
Figure BDA0003219788900000026
The measurement element of the multi-speed measurement equipment III is
Figure BDA0003219788900000027
The measurement element of the GNSS device is xt、yt、zt、
Figure BDA0003219788900000028
Establishing a functional relation between the measured element of the monopulse equipment and the measured element of the GNSS equipment:
Figure BDA0003219788900000029
wherein px, py, pz are station addresses of the single-pulse devices, and m' represents the time number;
establishing a functional relation between the measuring elements of the multi-speed measuring equipment and the measuring elements of the GNSS equipment:
Figure BDA00032197889000000210
wherein the content of the first and second substances,
Figure BDA00032197889000000211
representing the measurement cell, px, of the i' th multi-speed measuring devicei′,pyi′,pzi′Is the station address of the ith' multi-speed measuring equipment, px0Representing x-direction coordinates, ys, of the site of the transmitting station0Representing the y-direction coordinate of the site of the transmitting station, zs0Representing z-direction coordinates, R, of the site of the transmitting station0tIndicating the distance, R, of the target from the transmitting station at time ti′tThe distance between the target and the ith' multi-speed measuring equipment at the moment t is represented;
when a master station signal transmitting station and a receiving station of the multi-speed measuring equipment are the same station, the xs is taken0＝xs1、ys0＝ys1、zs0＝zs1、R0t＝R1t；
Establishing a functional relation between the measuring elements of the single-pulse equipment and the measuring elements of the multi-speed measuring equipment:
Figure BDA0003219788900000031
wherein x isct,yct,zctThe target position under the coordinate system of the measuring station of the multi-speed measuring equipment can be converted into x in the GNSS equipmentt,yt,zt,
Figure BDA0003219788900000032
Same coordinate system, denoted xdt,ydt,zdtThe velocity is obtained using the position difference:
Figure BDA0003219788900000033
wherein the content of the first and second substances,
Figure BDA0003219788900000034
representing the velocity in the x-direction at time t derived from the single pulse information difference,
Figure BDA0003219788900000035
representing the velocity in the y-direction at time t derived from the single pulse information difference,
Figure BDA0003219788900000036
representing the velocity in the z-direction, x, obtained by a single pulse information difference at time tdt+1Representing the target x coordinate, x, at time t +1dt-1Representing the target y coordinate at time t-1, ydt+1Representing the target y coordinate, y, at time t +1dt-1Representing the y coordinate of the target at time t-1, zdt+1Representing the target z coordinate, z, at time t +1dt-1Representing the target z coordinate at time t-1;
then there are:
Figure BDA0003219788900000037
in summary, there is the following formula:
Figure BDA0003219788900000038
the above equation has 9 equalities, and considering the measurement error of the observation device, the following inequality exists:
Figure BDA0003219788900000039
for the measurement of element RtThe number of involved inequalities is 4, so that the measurement element RtTotal number of consistency judgments of (P)it4; if the number of the inequalities is less than 2, the determination unit R is determinedtAn anomaly;
for element AtThe number of the involved inequalities is 4, so the measured element AtTotal number of consistency judgments of (P)it4; if the number of the inequalities is less than 2, determining the measurement element AtAn anomaly;
for element EtThe number of involved inequalities is 4, so the element E is measuredtTotal number of consistency judgments of (P)it4; if the number of inequalities is less than 2, determining the measurement element EtAn anomaly;
for measuring element
Figure BDA0003219788900000041
The number of involved inequalities is 2, so the measuring element
Figure BDA0003219788900000042
Total number of consistency judgments of (P)it2; if the number of the inequalities is less than 1, determining the measurement element
Figure BDA0003219788900000043
An anomaly;
for the test element xtThe number of involved inequalities is 6, so the measured element xtTotal number of consistency judgments of (P)it6; if the number of the inequalities is less than 3, determining the measurement element xtAn anomaly;
for element ztThe number of involved inequalities is 6, so the measured element ztTotal number of consistency judgments of (P)it6; if the number of the inequalities is less than 3, the determination unit z is determinedtAn anomaly;
for the measured element ytThe number of the involved inequalities is 5, so that the measured element ytTotal number of consistency judgments of (P)it(ii) 5; if the number of the inequalities is less than 3, the determination unit y is determinedtAn anomaly;
for measuring element
Figure BDA0003219788900000044
The number of involved inequalities is 3, so the measuring element
Figure BDA0003219788900000045
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure BDA0003219788900000046
An anomaly;
for measuring element
Figure BDA0003219788900000047
The number of involved inequalities is 3, so the measuring element
Figure BDA0003219788900000048
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure BDA0003219788900000049
An anomaly;
for measuring element
Figure BDA00032197889000000410
The number of involved inequalities is 3, so the measuring element
Figure BDA00032197889000000411
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure BDA00032197889000000412
And (6) abnormal.
Compared with the prior art, the invention has the following beneficial effects:
1) judging the data consistency by judging whether the functional relation between the test element and other data source test elements is in a normal range, accumulating consistency scores for different functional relations, and judging whether the test element is normal according to the consistency ratio; the method is suitable for three or more independent data sources, does not depend on the continuity of single data, and can identify most abnormal values; the method for judging the abnormal value of the isolated single data source has a good supplementary function, is effective to continuous or discontinuous abnormal values, and can reduce the probability of erroneous judgment of abnormal value identification.
2) The multi-source data consistency judging technology is added, so that the method has the capability of mutually judging the multi-source data, and the classical abnormal value identification method is supplemented from the data correlation angle, so that the method can be identified even if continuous multi-point abnormality or trend abnormality occurs, and the misjudgment and miscorrection conditions are few.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for identifying a multi-source data fusion abnormal value based on mutual consistency, which includes the following steps:
the method comprises the following steps: dividing the data into m data sources according to different observation devices, wherein the m data sources are different, and m is more than or equal to 3; the multi-source data are different source observed quantities of the same target. Data are divided according to independence of multi-source data, and are generally divided into different sources according to different observation devices. Suppose there are m different data sources, D respectively1、…、Dm。DiData source has niEach measurement element (measurement element for short) is
Figure BDA0003219788900000051
DjData source has njA measuring element is respectively
Figure BDA0003219788900000052
Step two: constructing a functional relation between every two data sources in the m data sources; the corresponding functional relationships established among the m different data sources are as follows:
Figure BDA0003219788900000053
due to the fact that
Figure BDA0003219788900000054
Because the measured value has a certain error, the measured value is correct
Figure BDA0003219788900000055
Then measure Yuan
Figure BDA0003219788900000056
And CikAnd if the test elements are consistent, the test elements can be mutually verified to be correct. DeltaikFor a given threshold, it can be based on the metric CikAnd
Figure BDA0003219788900000057
and functional relationship. i, j-1, 2, …, m, i ≠ j, k-1, 2, …, ni，niFor the ith data source DiNumber of middle measurement elements, njFor the jth data source DjThe number of middle test elements.
Step three: judging whether the test element in the data source is abnormal or not according to the functional relation; the abnormal value identification comprises the following specific steps:
s3.1, setting a test element CikIs given a consistency score of S ik0, the total number of consistency judgments Pik＝0；
S3.2 for data Source DiListing the data sources DiAnd the functional relation between all the measured elements and the measured elements of other data sources is as follows:
Figure BDA0003219788900000061
s3.3, judgment
Figure BDA0003219788900000062
Is true, wherein, δikIs a given threshold;
S3.4、Pik＝Pik+ 1; if the inequality is true, then measure element CikAnd
Figure BDA0003219788900000063
all the consistency scores of (1) are added, namely Sik＝Sik+1，Sj1＝Sj1+1,Sj2＝Sj2+1,...,Sjn＝Sjn+ 1; if the inequality is not true, the consistency score is unchanged;
s3.5, traversing the m data sources, traversing different measuring elements in the data sources, and judging
Figure BDA0003219788900000064
Whether the result is true or not;
s3.6 consistency ratio S to the final resultik/PikMaking a judgment if Sik/PikAnd if not less than 50%, judging that the measured element is normal, otherwise, judging that the measured element is abnormal.
Specific examples
If three kinds of observation equipment exist, m is 3, the observation equipment is single pulse equipment, multi-speed measurement equipment and GNSS equipment respectively, and one single pulse equipment, three multi-speed measurement equipment and one GNSS equipment are provided.
At time t, the measured element of the single-pulse device is Rt、At、EtThe measurement element of the multi-speed measurement equipment I is
Figure BDA0003219788900000065
The measurement element of the multi-speed measurement equipment II is
Figure BDA0003219788900000066
The measurement element of the multi-speed measurement equipment III is
Figure BDA0003219788900000067
The measurement element of the GNSS device is xt、yt、zt、
Figure BDA0003219788900000068
Three relations can be established according to the measuring element.
Establishing a functional relation between the measured element of the monopulse equipment and the measured element of the GNSS equipment:
Figure BDA0003219788900000069
where px, py, pz are the station addresses of the monopulse devices, and m' represents the number of times.
Establishing a functional relation between the measuring elements of the multi-speed measuring equipment and the measuring elements of the GNSS equipment:
Figure BDA00032197889000000610
wherein the content of the first and second substances,
Figure BDA00032197889000000611
representing the measurement cell, px, of the i' th multi-speed measuring devicei′,pyi′,pzi′Is the station address of the ith' multi-speed measuring equipment, px0Representing x-direction coordinates, ys, of the site of the transmitting station0Representing the y-direction coordinate of the site of the transmitting station, zs0Representing z-direction coordinates, R, of the site of the transmitting station0tIndicating the distance, R, of the target from the transmitting station at time ti′tAnd the distance between the target and the ith multi-speed measuring equipment at the moment t is shown. When a master station signal transmitting station and a receiving station of the multi-speed measuring equipment are the same station, the xs is taken0＝xs1、ys0＝ys1、zs0＝zs1、R0t＝R1t。
Establishing a functional relation between the measuring elements of the single-pulse equipment and the measuring elements of the multi-speed measuring equipment:
Figure BDA0003219788900000071
wherein x isct,yct,zctThe target position under the coordinate system of the measuring station of the multi-speed measuring equipment can be converted into x in the GNSS equipmentt,yt,zt,
Figure BDA0003219788900000072
Same coordinate system, denoted xdt,ydt,zdtThe velocity is obtained using the position difference:
Figure BDA0003219788900000073
wherein the content of the first and second substances,
Figure BDA0003219788900000074
representing the velocity in the x-direction at time t derived from the single pulse information difference,
Figure BDA0003219788900000075
representing the velocity in the y-direction at time t derived from the single pulse information difference,
Figure BDA0003219788900000076
representing the velocity in the z-direction, x, obtained by a single pulse information difference at time tdt+1Representing the target x coordinate, x, at time t +1dt-1Representing the target y coordinate at time t-1, ydt+1Representing the target y coordinate, y, at time t +1dt-1Representing the y coordinate of the target at time t-1, zdt+1Representing the target z coordinate, z, at time t +1dt-1Representing the target z coordinate at time t-1.
Then there are:
Figure BDA0003219788900000077
in summary, there is the following formula:
Figure BDA0003219788900000078
the above equation has 9 equalities, and considering the measurement error of the observation device, the following inequality exists:
Figure BDA0003219788900000079
for the measurement of element RtThe number of involved inequalities is 4, so that the measurement element RtTotal number of consistency judgments of (P)it4; if the number of the inequalities is less than 2, the determination unit R is determinedtAn anomaly; for element AtThe number of the involved inequalities is 4, so the measured element AtTotal number of consistency judgments of (P)it4; if the number of the inequalities is less than 2, determining the measurement element AtAn anomaly; for element EtThe number of involved inequalities is 4, so the element E is measuredtTotal number of consistency judgments of (P)it4; if the number of inequalities is less than 2, determining the measurement element EtAnd (6) abnormal.
For measuring element
Figure BDA0003219788900000081
The number of involved inequalities is 2, so the measuring element
Figure BDA0003219788900000082
Total number of consistency judgments of (P)it2; if the number of the inequalities is less than 1, determining the measurement element
Figure BDA0003219788900000083
And (6) abnormal.
For the test element xtThe number of involved inequalities is 6, so the measured element xtTotal number of consistency judgments of (P)it6; if the number of the inequalities is less than 3, determining the measurement element xtAn anomaly; for element ztThe number of involved inequalities is 6, so the measured element ztTotal number of consistency judgments of (P)it6; if the number of the inequalities is less than 3, the determination unit z is determinedtAn anomaly; for the measured element ytThe number of the involved inequalities is 5, so that the measured element ytTotal number of consistency judgments of (P)it(ii) 5; if the number of the inequalities is less than 3, the determination unit y is determinedtAn anomaly; for measuring element
Figure BDA0003219788900000084
The number of involved inequalities is 3, so the measuring element
Figure BDA0003219788900000085
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure BDA0003219788900000086
An anomaly; for measuring element
Figure BDA0003219788900000087
The number of involved inequalities is 3, so the measuring element
Figure BDA0003219788900000088
Uniformity ofTotal number of judgments Pit3; if the number of inequalities is less than 2, determining the measurement element
Figure BDA0003219788900000089
An anomaly; for measuring element
Figure BDA00032197889000000810
The number of involved inequalities is 3, so the measuring element
Figure BDA00032197889000000811
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure BDA00032197889000000812
And (6) abnormal.
Outlier identification correction is an indispensable step in the ballistic measurement data calculation process. When data is processed, the abnormal value of the observed data must be judged and processed firstly, and the quality of the processing result of the external data is ensured. The invention provides an identification method capable of effectively identifying continuous abnormal value points and reducing the misjudgment and miscorrection probability. The best mode for realizing the technology is to perform universalization and modularization processing on the multi-source data fusion abnormal value identification algorithm based on mutual consistency, unify input parameters and output parameters of the algorithm, perform modularization packaging on the algorithm, enable the algorithm to be easy to understand and use, and provide effective preprocessing for ballistic measurement data calculation processing.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (4)

1. A multisource data fusion abnormal value identification method based on mutual consistency is characterized by comprising the following steps:
the method comprises the following steps: dividing the data into m data sources according to different observation devices, wherein the m data sources are different, and m is more than or equal to 3;
step two: constructing a functional relation between every two data sources in the m data sources;
step three: and judging whether the test element in the data source is abnormal or not according to the functional relation.
2. The method for identifying the multi-source data fusion abnormal value based on the mutual consistency of the claims 1, wherein the function relationship between every two data sources in the m data sources is as follows:
Figure FDA0003219788890000011
wherein, CikFor the ith data source DiThe k-th cell of (1),
Figure FDA0003219788890000012
for the j-th data source, i, j is 1,2, …, m, i ≠ j, k is 1,2, …, ni，niFor the ith data source DiNumber of middle measurement elements, njFor the jth data source DjThe number of middle test elements.
3. The method for identifying the multisource data fusion abnormal value based on the mutual consistency as claimed in claim 2, wherein the method for judging whether the measured element in the data source is abnormal or not according to the functional relationship is as follows:
s3.1, setting a test element CikIs given a consistency score of Sik0, the total number of consistency judgments Pik＝0；
S3.2 for data Source DiListing the data sources DiAnd the functional relation between all the measured elements and the measured elements of other data sources is as follows:
Figure FDA0003219788890000013
s3.3, judgment
Figure FDA0003219788890000014
Is true, wherein, δikIs a given threshold;
S3.4、Pik＝Pik+ 1; if the inequality is true, then measure element CikAnd
Figure FDA0003219788890000015
all the consistency scores of (1) are added, namely Sik＝Sik+1，Sj1＝Sj1+1,Sj2＝Sj2+1,...,Sjn＝Sjn+ 1; if the inequality is not true, the consistency score is unchanged;
s3.5, traversing the m data sources, traversing different measuring elements in the data sources, and judging
Figure FDA0003219788890000016
Whether the result is true or not;
s3.6 consistency ratio S to the final resultik/PikMaking a judgment if Sik/PikAnd if not less than 50%, judging that the measured element is normal, otherwise, judging that the measured element is abnormal.
4. The mutual-consistency-based multi-source data fusion outlier identification method according to claim 1, wherein when m is 3, the observation devices are a single-pulse device, a multi-velocity measurement device and a GNSS device, and one single-pulse device, three multi-velocity measurement devices and one GNSS device are provided;
at time t, the measured element of the single-pulse device is Rt、At、EtThe measurement element of the multi-speed measurement equipment I is
Figure FDA0003219788890000017
The measurement element of the multi-speed measurement equipment II is
Figure FDA0003219788890000018
The measurement element of the multi-speed measurement equipment III is
Figure FDA0003219788890000019
The measurement element of the GNSS device is xt、yt、zt、
Figure FDA00032197888900000110
Establishing a functional relation between the measured element of the monopulse equipment and the measured element of the GNSS equipment:
Figure FDA0003219788890000021
wherein px, py, pz are station addresses of the single-pulse devices, and m' represents the time number;
establishing a functional relation between the measuring elements of the multi-speed measuring equipment and the measuring elements of the GNSS equipment:
Figure FDA0003219788890000022
wherein the content of the first and second substances,
Figure FDA0003219788890000023
representing the measurement cell, px, of the i' th multi-speed measuring devicei′,pyi′,pzi′Is the station address of the ith' multi-speed measuring equipment, px0Representing x-direction coordinates, ys, of the site of the transmitting station0Representing the y-direction coordinate of the site of the transmitting station, zs0Representing z-direction coordinates, R, of the site of the transmitting station0tIndicating the distance, R, of the target from the transmitting station at time ti′tThe distance between the target and the ith' multi-speed measuring equipment at the moment t is represented;
when a master station signal transmitting station and a receiving station of the multi-speed measuring equipment are the same station, the xs is taken0＝xs1、ys0＝ys1、zs0＝zs1、R0t＝R1t；
Establishing a functional relation between the measuring elements of the single-pulse equipment and the measuring elements of the multi-speed measuring equipment:
Figure FDA0003219788890000024
wherein x isct,yct,zctThe target position under the coordinate system of the measuring station of the multi-speed measuring equipment can be converted into x in the GNSS equipmentt,yt,zt,
Figure FDA0003219788890000025
Same coordinate system, denoted xdt,ydt,zdtThe velocity is obtained using the position difference:
Figure FDA0003219788890000026
wherein the content of the first and second substances,
Figure FDA0003219788890000027
representing the velocity in the x-direction at time t derived from the single pulse information difference,
Figure FDA0003219788890000028
representing the velocity in the y-direction at time t derived from the single pulse information difference,
Figure FDA0003219788890000029
representing the velocity in the z-direction, x, obtained by a single pulse information difference at time tdt+1Representing the target x coordinate, x, at time t +1dt-1Representing the target y coordinate at time t-1, ydt+1Representing the target y coordinate, y, at time t +1dt-1Representing the y coordinate of the target at time t-1, zdt+1Representing the target z coordinate, z, at time t +1dt-1Representing the target z coordinate at time t-1;
then there are:
Figure FDA00032197888900000210
in summary, there is the following formula:
Figure FDA0003219788890000031
the above equation has 9 equalities, and considering the measurement error of the observation device, the following inequality exists:
Figure FDA0003219788890000032
for the measurement of element RtThe number of involved inequalities is 4, so that the measurement element RtTotal number of consistency judgments of (P)it4; if the number of the inequalities is less than 2, the determination unit R is determinedtAn anomaly;
for element AtThe number of the involved inequalities is 4, so the measured element AtTotal number of consistency judgments of (P)it4; if the number of the inequalities is less than 2, determining the measurement element AtAn anomaly;
for element EtThe number of involved inequalities is 4, so the element E is measuredtTotal number of consistency judgments of (P)it4; if the number of inequalities is less than 2, determining the measurement element EtAn anomaly;
for measuring element
Figure FDA0003219788890000033
The number of involved inequalities is 2, so the measuring element
Figure FDA0003219788890000034
Total number of consistency judgments of (P)it2; if the number of the inequalities is less than 1, determining the measurement element
Figure FDA0003219788890000035
An anomaly;
for the test element xtThe number of involved inequalities is 6, so the measured element xtTotal number of consistency judgments of (P)it6; number of inequalityIf less than 3, determining the test element xtAn anomaly;
for element ztThe number of involved inequalities is 6, so the measured element ztTotal number of consistency judgments of (P)it6; if the number of the inequalities is less than 3, the determination unit z is determinedtAn anomaly;
for the measured element ytThe number of the involved inequalities is 5, so that the measured element ytTotal number of consistency judgments of (P)it(ii) 5; if the number of the inequalities is less than 3, the determination unit y is determinedtAn anomaly;
for measuring element
Figure FDA0003219788890000036
The number of involved inequalities is 3, so the measuring element
Figure FDA0003219788890000037
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure FDA0003219788890000041
An anomaly;
for measuring element
Figure FDA0003219788890000042
The number of involved inequalities is 3, so the measuring element
Figure FDA0003219788890000043
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure FDA0003219788890000044
An anomaly;
for measuring element
Figure FDA0003219788890000045
The number of involved inequalities is 3, so the measuring element
Figure FDA0003219788890000046
Total number of consistency judgments of (P)it3; if the number of inequalities is less than 2, determining the measurement element
Figure FDA0003219788890000047
And (6) abnormal.
CN202110954195.3A 2021-08-19 2021-08-19 Multi-source data fusion abnormal value identification method based on mutual consistency Pending CN113743480A (en)

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