CN109616224B - Track association confidence evaluation method, electronic equipment and storage medium - Google Patents

Abstract

The embodiment of the application provides a track association confidence evaluation method, electronic equipment and a storage medium, wherein the method comprises the following steps: calculating the distance between two tracks according to the track information reported by any two information sources; adding the two associated tracks serving as track pairs into a set to be evaluated; judging whether the association relation of the track pairs is correct or not by utilizing an iteration method according to the distance of the track pairs and the distance of each track in the information source of the track pairs; and determining the credibility of the track association according to the judgment result. According to the technical scheme, the distances of the tracks reported by the two information sources are iteratively compared, the track pairs with correct association relations and incorrect association relations are determined, the association confidence degrees of all the track pairs are finally obtained, the purpose of evaluating the credibility degree of the track association result is achieved, and the credibility reference is provided for the information processing process based on the track association result.

Description

Track association confidence evaluation method, electronic equipment and storage medium

Technical Field

The present application relates to the field of track association confidence evaluation, and in particular, to a track association confidence evaluation method based on nearest distance matching, an electronic device, and a computer storage medium.

Background

The track association refers to a process of establishing a mutual association relationship between tracks reported by different information sources. The credibility of the track association determines the effectiveness of the air situation, and has important influence on the track fusion performance. However, it is difficult to objectively evaluate the accuracy and reliability of the track-related result due to the lack of a uniform evaluation criterion for the track-related result. Particularly, in a dense target scene, the credibility of the track correlation result is greatly reduced. An evaluation method of the track association confidence for dense target scenes is still lacked in engineering application.

Disclosure of Invention

To solve one of the above problems, the present application provides a method, an electronic device, and a computer storage medium for estimating a confidence of a track association based on a closest distance matching.

According to a first aspect of the embodiments of the present application, there is provided a method for estimating a track association confidence, the method including the steps of:

calculating the distance between two tracks according to the track information reported by any two information sources;

adding the two associated tracks serving as track pairs into a set to be evaluated;

judging whether the association relation of the track pairs is correct or not by utilizing an iteration method according to the distance of the track pairs and the distance of each track in the information source of the track pairs;

and determining the credibility of the track association according to the judgment result.

According to a second aspect of embodiments of the present application, there is provided an electronic apparatus, including: a memory, one or more processors; the memory is connected with the processor through a communication bus; the processor is configured to execute instructions in the memory; the storage medium has stored therein instructions for carrying out the steps of the method as described above.

According to a third aspect of embodiments of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the method as described above

According to the technical scheme, the distances of the tracks reported by the two information sources are iteratively compared, the track pairs with correct association relations and incorrect association relations are determined, the association confidence degrees of all the track pairs are finally obtained, the purpose of evaluating the credibility degree of the track association result is achieved, and the credibility reference is provided for the information processing process based on the track association result.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 shows a schematic diagram of a track association confidence evaluation method according to the present embodiment.

Detailed Description

In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

The core idea of the scheme is that information sources such as equipment (such as radar) for providing tracks from the outside are utilized and input into a computer through a data transmission medium (such as a network cable); and the computer processor compares the distances between the information source tracks according to the tracks input by the information source to judge the credibility of the correlation result of the specific track, thereby providing a basis for multi-source information fusion and comprehensive identification.

As shown in fig. 1, the present disclosure provides a method for evaluating a track association confidence based on a closest distance matching, which mainly includes:

firstly, aiming at any two tracks reported by two information sources, calculating the distance between the two tracks

Aiming at any two information sources i and j, if the flight path s reported by the information source i_ipIs in the position of [ x_ip,y_ip,z_ip]Track s reported by information source j_jqIs in the position of [ x_jq,y_jq,z_jq]Then calculate s_ipAnd s_jqDistance d(s) of_ip,s_jq) Comprises the following steps:

secondly, calculating the associated confidence of any two associated tracks by a track associated confidence calculation module

Let s be for any two information sources i and j_ipAnd s_jqRespectively representing the tracks reported by the information source i and the information source j. With I(s)_ip,s_jq) Represents the flight path s reported by the information source i_ipFlight path s reported with information source j_jqAnd (6) correlating the results. I(s)_ip,s_jq) 1 denotes track s_ipAssociated track s_jq，I(s_ip,s_jq) Track 0 s_ipUncorrelated flight paths s_jq. All I(s)_ip,s_jq) Track pair(s) corresponding to 1_ip,s_jq) Adding to the set to be evaluated Λ_eva＝{(s_ip,s_jq)|I(s_ip,s_jq) 1 }. Then, adopting an iterative method to calculate Lambda_evaMiddle track pair(s)_ip,s_jq) The specific method of the correlation confidence of (2) is as follows:

in 1 st iteration, initializing evaluation set of k th iteration to be lambda^k _eva＝Λ_eva。

At the k-th>In 1 iteration, first, the k-th iteration evaluation set is initialized to be lambda^k _eva＝Λ^k-1 _eva。

Second, for Λ^k _evaArbitrary track pair(s)_ip,s_jq) Respectively, in the information source j and s_ipThe closest flight path s_ip,j ^*And with s in information source i_jqThe closest flight path s_jq,i ^*. If s_jq＝s_ip,j ^*And s_ip＝s_jq,i ^*Then put si_pAnd s_jqAssociated confidence of U(s)_ip,s_jq) 1, represents si_pAnd s_jqIs correct, and will(s)_ip,s_jq) From Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)}。

Then, if Λ^k _evaIf the set is empty, the algorithm is ended; if Λ^k _evaNot empty set, for Λ^k _evaArbitrary track pair(s)_ip,s_jq) Si of (2)_pCalculating the distance si in the information source j_pRatio s_jqCloser set Λ^k _eva-sip＝{s_jq,c|d(s_ip,s_jq,c)<d(s_ip,s_jq)}. If s in the set exists_jq,cSo that s_jq,cSetting U(s) without associating with the track reported by any information source i_ip,s_jq) 0 denotes the track s_ipAnd s_jqIs wrong, and will(s)_ip,s_jq) From Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)}. To(s)_ip,s_jq) S of_jqCalculating the distance s in the information source i_jqRatio s_ipCloser set Λ^k _eva-sjq＝{s_ip,c|d(s_ip,c,s_jq)<d(s_ip,s_jq)}. If s in the set exists_ip,cSo that s_ip,cSetting U(s) without associating with the track reported by any information source j_ip,s_jq) 0, denotes the track si_pAnd s_jqIs wrong, and will(s)_ip,s_jq) From Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)}。

Then, if Λ^k _evaIf the set is empty or contains only a single element, the algorithm ends; if Λ^k _evaContaining two or more elements, for any two track pairs(s)_ip,s_jq) And(s)_ip',s_jq'), if d(s)_ip，s_jq')+d(s_ip',s_jq)<d(s_ip，s_jq)+d(s_ip',s_jq') and simultaneously placing U(s)_ip,s_jq)＝0，U(s_ip',s_jq') 0, two track pairs(s)_ip,s_jq) And(s)_ip',s_jq') all are wrong, and will be(s)_ip,s_jq) And(s)_ip',s_jq') from Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)，(s_ip',s_jq')}。

Finally, judging whether the iteration process is stopped: if Λ^k _evaAnd Λ^k-1 _evaIf not, continuing to perform the next iteration; if Λ^k _evaAnd Λ^k-1 _evaSame, then set to Λ^k _evaAll track pairs(s) in_ip,s_jq) Associated confidence of U(s)_ip,s_jq) 0.5 indicates that the track pair(s) cannot be determined_ip,s_jq) And if the association relation is correct, finishing the algorithm.

According to the scheme, a track association confidence evaluation system based on the closest distance matching can be constructed as required, and the system comprises: the system comprises an information source track calculation module and a track association confidence calculation module. Firstly, calculating the distance between any two tracks reported by any two information sources through an information source track calculation module; and then, evaluating the association confidence degrees of the two associated tracks aiming at the two information sources through a track association confidence degree calculation module.

In this scheme, the track association confidence evaluation method may also implement its evaluation function through an electronic device, where the electronic device includes: a memory, one or more processors; the memory is connected with the processor through a communication bus; the processor is configured to execute instructions in the memory; the storage medium has stored therein instructions for carrying out the steps of the method as described above.

In this embodiment, the method for estimating the track-related confidence may also be recorded in a computer-readable storage medium, and a computer program stored on the computer-readable storage medium implements the estimating function, and when the program is executed by a processor, the method implements the steps of the method.

According to the technical scheme, the track association confidence evaluation method determines the track pairs with correct association relation and wrong association relation by iteratively comparing the distances of the tracks reported by the two information sources, finally obtains the association confidence of all the track pairs, achieves the purpose of evaluating the credibility of the track association result, and provides credibility reference for the information processing process based on the track association result.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (5)

1. A method for evaluating a confidence of track association is characterized by comprising the following steps:

calculating the distance between two tracks according to the track information reported by any two information sources;

adding the two associated tracks serving as track pairs into a set to be evaluated;

judging whether the association relation of the track pairs is correct or not by utilizing an iteration method according to the distance of the track pairs and the distance of each track in the information source of the track pairs;

determining the credibility of the track association according to the judgment result;

in the step of calculating the distance between two tracks according to any two track information: the distance between the two tracks is:

wherein, any two information sources i and j, flight path s reported by the information source i_ipIs in the position of [ x_ip,y_ip,z_ip]Track s reported by information source j_jqIs in the position of [ x_jq,y_jq,z_jq]；

The step of adding the two associated tracks as track pairs into the set to be evaluated comprises the following steps:

flight path s reported by information source i_ipFlight path s reported with information source j_jqIs expressed as I(s)_ip,s_jq) Wherein, I(s)_ip,s_jq) 1 denotes track s_ipAssociated track s_jq，I(s_ip,s_q) Track s is represented by 0_ipUncorrelated flight paths s_jq；

All I(s)_ip,s_jq) Track pair(s) corresponding to 1_ip,s_jq) Adding to a set to be evaluated:

Λ_eva＝{(s_ip,s_jq)|I(s_ip,s_jq)＝1}；

the step of judging whether the association relationship of the track pairs is correct or not by using an iteration method according to the distance of the track pairs and the distance of each track in the information source comprises the following steps:

in 1 st iteration, initializing evaluation set of k th iteration to be lambda^k _eva＝Λ_eva；

At the k-th>Initializing the k-th iteration evaluation set to be lambda in 1 iteration^k _eva＝Λ^k-1 _eva；

For Λ^k _evaArbitrary track pair(s)_ip,s_jq) Respectively, in the information source j and s_ipThe closest flight path s_ip,j ^*And with s in information source i_jqThe closest flight path s_jq,i ^*(ii) a If s_jq＝s_ip,j ^*And s_ip＝s_jq,i ^*Then set to s_ipAnd s_jqAssociated confidence of U(s)_ip,s_jq) 1 denotes s_ipAnd s_jqIs correct, and will(s)_ip,s_jq) From Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)}；

If Λ^k _evaIf the set is empty, the algorithm is ended;

if Λ^k _evaNot empty set, for Λ^k _evaArbitrary track pair(s)_ip,s_jq) S of_ipCalculating the distance s in the information source j_ipRatio s_jqCloser set Λ^k _eva-sip＝{s_jq,c|d(s_ip,s_jq,c)<d(s_ip,s_jq) }; if s in the set exists_jq,cSo that s_jq,cSetting U(s) without associating with the track reported by any information source i_ip,s_jq) 0 denotes the track s_ipAnd s_jqIs wrong, and will(s)_ip,s_jq) From Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)}；

If Λ^k _evaNot empty set, for Λ^k _evaArbitrary track pair(s)_ip,s_jq) S of_jqCalculating the distance s in the information source i_jqRatio s_ipCloser set Λ^k _eva-sjq＝{s_ip,c|d(s_ip,c,s_jq)<d(s_ip,s_jq) If s in the set exists_ip,cSo that s_ip,cSetting U(s) without associating with the track reported by any information source j_ip,s_jq) 0 denotes the track s_ipAnd s_jqIs wrong, and will(s)_ip,s_jq) From Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)}。

2. The track association confidence evaluation method according to claim 1, wherein the step of determining whether the association relationship of the track pair is correct by using an iterative method according to the distance of the track pair and the distance of each track in the information source further comprises:

if Λ^k _evaIf the set is empty or contains only a single element, the algorithm ends; if Λ^k _evaContaining two or more elements, for any two track pairs(s)_ip,s_jq) And(s)_ip',s_jq'), if d(s)_ip，s_jq')+d(s_ip',s_jq)<d(s_ip，s_jq)+d(s_ip',s_jq') and simultaneously placing U(s)_ip,s_jq)＝0，U(s_ip',s_jq') 0, two track pairs(s)_ip,s_jq) And(s)_ip',s_jq') all are wrong, and will be(s)_ip,s_jq) And(s)_ip',s_jq') from Λ^k _evaOf (A) removal, i.e.' A^k _eva＝Λ^k _eva/{(s_ip,s_jq)，(s_ip',s_jq')}。

3. The track association confidence evaluation method according to claim 2, wherein the step of determining whether the association relationship of the track pair is correct by using an iterative method according to the distance of the track pair and the distance of each track in the information source further comprises:

judging whether the iteration process is stopped: if Λ^k _evaAnd Λ^k-1 _evaIf not, continuing to perform the next iteration; if Λ^k _evaAnd Λ^k-1 _evaSame, then set to Λ^k _evaAll track pairs(s) in_ip,s_jq) Associated confidence of U(s)_ip,s_jq) 0.5 indicates that the track pair(s) cannot be determined_ip,s_jq) And if the association relation is correct, finishing the algorithm.

4. An electronic device, the electronic device comprising: a memory, one or more processors; the memory is connected with the processor through a communication bus; the processor is configured to execute instructions in the memory; the memory has stored therein instructions for carrying out the steps of the method according to any one of claims 1 to 3.

5. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 3.

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