Tracking Move-Stop-Move Targets with State-Dependent Mode Transition Probabilities

摘要

This paper presents a novel method for tracking ground moving targets with a GMTI radar. To avoid detection by the GMTI radar, targets can deliberately stop for some time before moving again. The GMTI radar does not detect a target when the radial velocity (along the line-of-sight from the sensor) falls below a certain minimum detectable velocity (MDV). We develop a new approach by using state-dependent mode transition probabilities to track move-stop-move targets. Since in a real scenario, the maximum deceleration is always limited, a target can not switch to the stopped-target model from a high speed. Therefore, with the use of the stopped-target model, the Markov chain of the mode switching has jump probabilities that depend on the target's kinematic state. A mode transition matrix with zero jump probabilities to the stopped-target mode is used when the speed is above a certain "stopping" limit (above which the target cannot stop in one sampling interval, designated as "fast stage") and another transition matrix with non-zero jump probabilities to the stopped-target mode is used when the speed is below this limit (designated as "slow stage"). The stage probabilities are calculated using the kinematic state statistics from the IMM estimator and then used to combine the state-dependent mode transition probabilities (SDP) in the two different transition matrices. The experimental results show that the proposed algorithm outperforms previous methods.