CN102645646B - Uncertain fusion location method of multiple information sources - Google Patents

Abstract

The invention discloses an uncertain fusion location method of multiple information sources, which belongs to the technical field of intelligent information processing and is used for resolving the problems of fusion and location of multi-source monitoring information under the effect of uncertain factors in an actual system. The uncertain fusion location method considers the uncertain factors as relative noise with uncertain items, and obtains uncertain fusion algorithm of the multi-source monitoring information. The algorithm only needs to conduct once global approximation on the uncertain factors in the system, and the uncertain fusion location method reduces calculated amount, improves fusion accuracy and achieves accurate location of targets accordingly.

Description

The uncertain fusion and positioning method of a kind of multiple source

Technical field

The present invention relates to a kind of fusion and positioning method, the particularly fusion and positioning method of a kind of multiple source under uncertain noise belongs to the intelligent information processing technology field.

Background technology

Along with going deep into of low altitude airspace administrative reform, the General Aviation of China enters the fast-growing period, and the increase day by day of all purpose aircraft makes the low altitude airspace flying activity become more and more intricate, thereby has brought new challenge for low-altitude detection and security monitoring.

Radar is with its intrinsic characteristics, it is the necessaries of low latitude blank pipe, due to the rectilinear propagation of radar wave and the impact of landform shelter, when being monitored, airbound target has a large amount of radar shadow, limited the raising of tracking accuracy and the ability that short-term collision detects alarm.The auxiliary supervision of low null images can be followed the tracks of low target, spreadability is good, but the climate impact is larger, the auxiliary supervision cooperation of image radar tracking system can be realized the collaborative supervision to aerial target, obtain the exact position of target by Data fusion technique, and then the tracking low target, the reliability of raising surveillance.

Raising to target tracking accuracy and system reliability requirement makes single-measurement can't satisfy, and utilizes the multi-source information of multisensor to merge to target the focus that the location has become present research.The JPDA method of multisensor and be the target following localization method of commonly using based on many hypothesis tracing of Interactive Multiple-Model, document " " based on infrared and maneuvering target tracking method Radar Data Fusion "; Zhu Zhiyu; laser and infrared; in February, 2007, the 37th volume, the 2nd phase; 170-174 " utilizes parallel multisensor JPDA method, by infrared fusion with radar data being realized the track and localization to target.But these fusion and positioning methods are mainly the hypothesis of independent white Gaussian noise based on the measuring error of multisensor, and condition is too desirable.In reality, radar and vision monitoring equipment usually are placed on a platform, and the error of platform position angle and angular altitude has caused image and radargrammetry noise to have correlativity, and noise statistics can not be known for people, exists various uncertain factors; If ground is furnished with a plurality of surveillances, merging needs equivalence to the same coordinate system when estimating, this equivalence also can bring relevance error and uncertain error when the monitoring point distance is larger.Practice shows, these relevance errors and uncertainty are usually the principal elements of impact fusion estimated accuracy.And the present fusion and positioning method of giving can't be considered the uncertain factor in real system, description real system that can not be properer.

Summary of the invention

The object of the invention is to for the deficiencies in the prior art, the fusion and positioning method of the lower multiple source of a kind of uncertain factor impact is provided, the fusion that obtains multi-source information by the coefficient weighting matrix under the impact of calculating uncertain factor is estimated, realizes the fusion location to target.

The technical solution adopted in the present invention is the uncertain fusion and positioning method of a kind of multiple source, and characteristics specifically comprise the following steps:

1, contain correlation noise and indeterminate mIndividual sensor provides the model of Same Physical vector

kTConstantly merge and estimate to be defined as

In formula:

Be physical vector to be estimated, Be the fusion estimated result,

For

Constantly the The measured value of individual sensor,

Be corresponding measuring error, average is zero,

Covariance matrix be

,

Expression Constantly the

The indeterminate of individual sensor measurement,

Be matrix of coefficients,

Be the sampling period, full application form symbol definition is identical;

2, according to the covariance matrix of surveying instrument and the given measuring error of error calibration, calculate

Sub-block in formula

The expression measuring error

Covariance matrix,

Be the supremum of uncertain error, EThe expression mathematical expectation, real parameter

Determine by concrete system and experiment;

3, basis

Determine to merge the estimation coefficient matrix

,

In formula:

,

,

Be unit matrix;

4 kTFusion estimated value constantly

And the error covariance matrix that merges estimation

For:

。

The invention has the beneficial effects as follows: the present invention considers the impact of uncertain factor in the measurement of multi-source monitoring system, more press close to real system, in order to dwindle the impact of uncertain factor, uncertain factor is thought of as to measure noise interrelated and with indeterminate, this blending algorithm only needs Integratively approximate to uncertain factor, avoided the measured value of each sensor is estimated through filtering and each filtering needs a large amount of calculating that indeterminate is similar to, simplify calculated amount, improved the precision that target is merged the location.

Below in conjunction with drawings and Examples, the present invention is elaborated.

Description of drawings

Fig. 1 is that process flow diagram is estimated in the uncertain fusion of multiple source, and the symbol in figure is consistent with symbol in instructions.

Embodiment

With reference to Fig. 1.

The below is to illustrate this fusion and positioning method to the supervision of low flyer as example, hypothetical target is monitored jointly by radar and image, two kinds of surveillance equipments are arranged on identical platform, the error of platform position angle and angular altitude causes image and radargrammetry noise to have correlativity, and there is uncertain factor in the statistical property of noise.Metrical information by radar and image is traced and monitored low flyer, need to merge the location to the metrical information of radar and image, and concrete steps are as follows:

1, with the measurement data equivalence of radar and image monitoring system in the coordinate system of reference observation point, provide the model of the Same Physical vector that contains correlation noise and indeterminate,

kTConstantly merge and estimate to be defined as

In formula

For treating the positional information of estimating target,

Represent respectively oblique distance, position angle and the angular altitude of target;

Be the measured value of radar and image monitoring system,

Oblique distance, position angle and the angular altitude of the target of gained measured in expression respectively;

Be

Measuring error, average is zero, Covariance matrix be

Indeterminate for radar and vision monitoring equipment measurement;

For merging the estimation coefficient matrix;

Be the fusion estimated result, Oblique distance, position angle and the angular altitude of the target of gained merged in expression respectively;

Be the sampling period;

2, according to the covariance matrix of surveying instrument and the given measuring error of error calibration, calculate

，

In formula

Sub-block

The expression measuring error

Covariance matrix;

Be the supremum of uncertain error, EThe expression mathematical expectation;

Real parameter

Determine by concrete system and experiment;

3, basis

Determine to merge the estimation coefficient matrix

In formula:

，

，

Be unit matrix;

4, kTFusion estimated value constantly

And the error covariance matrix that merges estimation

For:

，

。

Claims (1)

1. the uncertain fusion and positioning method of multiple source, is characterized in that comprising the steps:

(a) contain correlation noise and indeterminate mIndividual sensor provides the model of Same Physical vector

kTConstantly merge and estimate to be defined as

In formula:

Be physical vector to be estimated,

Be the fusion estimated result,

,

For

Constantly the

The measured value of individual sensor,

Be corresponding measuring error, average is zero,

Covariance matrix be

,

Expression

Constantly the

The indeterminate of individual sensor measurement,

Be matrix of coefficients,

Be the sampling period;

(b) according to the covariance matrix of surveying instrument and the given measuring error of error calibration, calculate

In formula: sub-block

The expression measuring error

Covariance matrix,

Be the supremum of uncertain error, EThe expression mathematical expectation, real parameter

Noise statistics and concrete experiment by real system are determined;

(c) basis

Determine to merge the estimation coefficient matrix

,

In formula:

,

,

Be unit matrix;

(d) kTFusion estimated value constantly

And fusion evaluated error covariance matrix

For:

。

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