基于数据质量评估的自适应序贯航迹关联算法

doi:10.12305/j.issn.1001-506X.2022.11.23

Abstract

Abstract:

In order to solve the track-association problem when sensor suffers declined accuracy, an adaptive sequential track-association algorithm based on data quality assessment is proposed. Real-time data quality evaluation results are introduced into the adjustment of correlation threshold. The entropy method and the utility function method are combined to evaluate the performance of sensor and the quality of filtering, and the fuzzy control relationship between two indexes and the significance level is constructed, so as to realize the adaptive adjustment of correlation threshold. The simulation results show that the performance of the improved algorithm is better than that of compared algorithm in the situation of declined sensor accuracy, and the good correlation effect is beneficial to the improvement of fusion accuracy.It also has good adaptability in the case of maneuver target tracking.

Key words: multi-source information fusion, data quality assessment, track-association, entropy method, fuzzy control

CLC Number:

V243.2
TN953

Yu ZHANG, Kai WU, Jie GUO, Zhishan GE, Baochao ZHANG. Adaptive sequential track-association algorithm based on data quality assessment[J]. Systems Engineering and Electronics, 2022, 44(11): 3477-3485.

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α		C₂
α		PS	PMS	PM	PMB	PB
C₁	PS	PB	PB	PB	PMB	PM
	PMS	PB	PB	PMB	PM	PMS
	PM	PB	PMB	PM	PMS	PS
	PMB	PMB	PM	PMS	PS	PS
	PB	PM	PMS	PS	PS	PS

参数	值	参数	值
σ_max^r/m	200	σ_min^r/m	10
σ_max^β/(°)	5	σ_min^β/(°)	0.1
σ_max^ε/(°)	5	σ_min^ε/(°)	0.1
D_max/m	50	D_min/m	1

目标	参数	值
目标1	初始位置/km	(30, 7.5, 30)
	初始速度/(m/s)	(-100, 0, 0)
	加速度/(m/s²)	(-0.5, 0, 0)
目标2	初始位置/km	(20, 7.5, 30)
	初始速度/(m/s)	(-100, 0, 0)
	纵向机动幅值A₁/(m/s²)	0.2g(g为重力加速度)
	纵向机动频率w₁/Hz	20
	横向机动幅值A₂/(m/s²)	0.2g
	横向机动频率w₂/Hz	5

参数	雷达1		雷达2
参数	标准精度	受干扰时精度	雷达2
距离量测精度/m	30	150	50
高低角量测精度/(°)	0.3	1.5	0.5
方位角量测精度/(°)	0.3	1.5	0.5

探测源/算法	融合距离RMSE/m	融合高低角RMSE/(°)	融合方位角RMSE/(°)
雷达1量测	58.561 4	0.616 8	0.770 3
雷达2量测	49.955 1	0.445 0	0.530 1
ASTA	18.740 0	0.177 5	0.169 4
STA	28.363 1	0.288 6	0.290 7
Grey算法	19.468 5	0.166 1	0.211 3

Adaptive sequential track-association algorithm based on data quality assessment

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探测源/算法	融合距离RMSE/m	融合高低角RMSE/(°)	融合方位角RMSE/(°)
雷达1量测	71.892 9	0.754 1	0.628 1
雷达2量测	50.045 7	0.526 7	0.490 3
ASTA	19.515 8	0.169 6	0.227 9
STA	28.008 8	0.237 8	0.319 6
Grey算法	23.290 1	0.194 8	0.237 0