Abstract
Because the varieties of general aviation aircraft and their performance differences become increasingly large, the traditional multiple model tracking algorithm needs to employ more motion models to describe the actual maneuver model of a moving target. This fact is easy to degrade the tracking accuracy and brings a large computational load. Thus, a target classification aided variable-structure multiple-model algorithm (TCA-VSMM) is proposed to solve the above problem. In the proposed TCA-VSMM algorithm, the target classification aided is introduced to improve the accuracy of state estimation. Then, the target classification aided in the screening of the motion model set is analyzed. Concretely, the target classification information and velocity information in automatic dependent surveillance-broadcast (ADS-B) measurements are incorporated into the variable-structure multiple-model filter. Consequently, the screening model set is more approximated to the real motion model of a moving target. Experiments show that the TCA-VSMM algorithm can obtain better performance with small computation load and high estimation accuracy than those of the model-group switching variable-structure multiple-model algorithm.
Highlights
INTRODUCTIONThe tracking filter is the mathematical calculation procedure
Under the target tracking, the tracking filter is the mathematical calculation procedure
The basic theory of TCA-Variable-Structure Multiple-Model (VSMM) is introduced in the third part; in the fourth part, a TCA-VSMM algorithm is proposed for the problem of overlarge motion model set caused by various classification of general aviation aircraft and maneuvering modes, conducted experiments; the conclusion of this paper is drawn in the fifth part
Summary
The tracking filter is the mathematical calculation procedure. The TCA-VSMM algorithm for target classification aided adjustment of the motion model set is generally divided into two parts: the acquisition and processing of information and the multiplemodel filtering. This paper analyzes why employing the target classification information to filter the model set in the multiple-model algorithm can add the accuracy of the estimation and reduce the estimated Root Mean Square Error (RMSE) Based on this theory, this paper studies the specific application of the TCA-VSMM algorithm in ADS-B data filtering from the general aviation monitoring system. Third part; in the fourth part, a TCA-VSMM algorithm is proposed for the problem of overlarge motion model set caused by various classification of general aviation aircraft and maneuvering modes, conducted experiments; the conclusion of this paper is drawn in the fifth part. It is theoretically proved that the introduction of target classification screening can make the model set during the multiple-model filtering process closer to the optimal model set, thereby improving the performance of the multiple-model algorithm
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