A novel radar radiation control strategy based on passive tracking in multiple aircraft platforms

Abstract

This paper proposes a radar radiation control method based on cooperation tracking of multiple sensors. The main idea of the method is passive tracking in multiple platforms is used preferentially, while radar tracks target timely according to the tracking accuracy. In this paper, a tracking accuracy metric called interactive multiple model predicted covariance (IMMPC) is derived by IMM-EKF algorithm. By comparing with the pre-defined threshold, whether or not the radar transmitter radiates energy is determined. Simulation results show that the proposed radiation control method can reduce the radar radiation times effectively and have a good performance of low probability of interception (LPI).

Novel Power Control Scheme for Target Tracking in Radar Network with Passive Cooperation

“…On the other hand, in [28], only the minimization of total transmitted power for radar networks is considered. From the previous results in [26], [28], we can conclude that the revisit interval affects the target tracking accuracy, and the transmitted power affects the target detection performance during tracking process. Therefore, the LPI performance for target tracking in DRNS can be improved by jointly optimizing the radar revisit interval and the transmitted power for a predefined target tracking accuracy, where the fewer number of total radiation times and lower transmitted power leads to smaller transmission power consumption.…”

“…Later, Zhang et al [25] developed an optimal sensor selection strategy based on passive sensor cooperation, and it was shown that the proposed algorithm can decrease the radar radiation times with excellent target tracking accuracy. Chen et al extended the results of the previous research and presented a radar radiation control strategy for multiple aircraft platforms based on time difference of arrival (TDOA) cooperation [26], which utilized the comparison of covariance and the predefined threshold to control the radiation state [27]. Overall speaking, the reported works verified that adaptive transmit parameters control was an effective technique to improve the LPI performance for radar systems.…”

“…Technically speaking, low transmit power, short dwell time, large revisit interval, and ultra-low side lobe antenna will lead to better LPI performance. Thus, the problem of LPI based radar resource scheduling in traditional monostatic radars has been extensively studied from various perspectives [20][21][22][23][24][25][26] [26]. In [24], a novel radar energy control algorithm based on an improved interacting multiple model particle filtering (IMMPF) was formulated for LPI performance enhancement, which controlled the radiation time and power of radar according to the target's range and radar cross section (RCS) with a given probability of target detection.…”

“…The work in [26] concentrates on the maximization of the revisit interval based on TDOA cooperation, whereas the transmit power control is ignored. On the other hand, in [28], only the minimization of total transmitted power for radar networks is considered.…”

Joint Transmitter Selection and Resource Management Strategy Based on Low Probability of Intercept Optimization for Distributed Radar Networks

“…In Wang et al (), Wang et al propose a joint revisit and dwell time management strategy for single‐target tracking based on the predicted Bayesian Cramer‐Rao lower bound in‐phased‐array radar system, where the resource burden is minimized with the target‐tracking performance, meeting a specified threshold. Also, LPI‐based radar resource‐aware design for target tracking has been addressed in multiple‐target tracking (Zhang et al, ) and multisensor selection scenarios (J. Chen et al, ; Kalandros & Pao, ; Puranik & Tugnait, ).…”