基于量测转换序贯滤波的GMPHD机动目标跟踪

doi:10.12305/j.issn.1001-506X.2022.08.11

Abstract

Abstract:

For multiple maneuvering targets tracking by Doppler radar in clutter, a multiple model Gaussian probability hypothesis density algorithm based on decorrelated unbiased converted measurement sequential filter is proposed. For the nonlinearity of the measurements, the position measurements are converted to unbiased measurements, and the Doppler measurement is converted to debiased pseudo measurement, and the tracking accuracy is improved by sequential filtering. For the maneuverability of the target, the idea of multiple model is introduced into Gaussian mixture probability hypothesis density (GMPHD), where the Gaussian components related to the model are predicted and updated. Simulation results demonstrate that the proposed algorithm can achieve effective maneuvering multi-target tracking in clutter. Compared with unscented Kalman multiple model GMPHD, the tracking accuracy is increased by 38.15%, and the algorithm efficiency is greatly improved. Compared with unscented Kalman best-fitting Gaussian approximation GMPHD, the efficiency is slightly increased, and the tracking accuracy is improved by 36.47%.

Key words: Gaussian mixture probability hypothesis density, multiple model, multiple target tracking, maneuvering target tracking, nonlinear measurement

CLC Number:

TN953

Zilin HOU, Ting CHENG, Han PENG. GMPHD based on measurement conversion sequential filtering for maneuvering target tracking[J]. Systems Engineering and Electronics, 2022, 44(8): 2474-2482.

Figures/Tables 12

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References 30

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目标	出现时刻/s	出现位置/m	消失时刻/s	机动
1	1	[50, 200]	100	1~100 s匀速
2	31	[100, 250]	70	31~40 s匀速, 41~60 s匀速左转弯, 61~70 s匀速
3	11	[150, 350]	90	11~30 s匀速, 31~60 s匀速右转弯, 61~90 s匀速
4	21	[300, 250]	80	21~80 s匀速左转弯

滤波改变参数	UK-MM-GMPHD/%	UK-BFG-GMPHD/%
λ=0.5×10^－4/m²	36.99	36.71
λ=2×10^－4/m²	40.36	38.88
P_d=0.79	64.61	38.24
P_d=0.89	55.47	41.15
P_s=0.79	39.86	38.45
P_s0.89	42.08	36.29

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GMPHD based on measurement conversion sequential filtering for maneuvering target tracking

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