LPI-constrained collaborative transmit beampattern optimization and resource allocation for maneuvering targets tracking in colocated MIMO radar network - Su, Yang; Cheng, Ting; He, Zishu (Signal processing, 2023)
•This work addresses a low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) for multiple maneuvering targets tracking (MMTT) in the colocated MIMO radar network.•In the proposed LPI-CBORA problem for maneuvering targets tracking, the LPI is achieved via adaptively controlling the distribution of the transmit energy in the airspace for the first time.•We formulate the LPI-CBORA as a nonconvex optimization problem, where the node-target assignment, beampattern design and bandwidth allocation are collaboratively considered for the first time.•A two-stage solution algorithm incorporating with the successive convex approximation and the cyclic minimization algorithm is proposed to solve the LPI-CBORA-related problem efficiently. Considering tracking multiple maneuvering targets with the presence of a hostile interceptor in the modern electronic warfare (EW) environment, how to maximize targets tracking performance while ensuring system’s anti-interception capability is of essential significance for the radar network consisting of multiple colocated MIMO radar (CMR) nodes. In this paper, we propose a novel low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) strategy for multiple maneuvering targets tracking (MMTT) in the CMR network (CMRN). More precisely, the LPI-CBORA strategy is formulated as a nonconvex optimization problem, where the node-target assignment, beampattern design and bandwidth allocation are collaboratively considered for the first time. To tackle the nonconvex problem effectively, an efficient two-stage solution algorithm incorporating with the successive convex approximation (SCA) and the cyclic minimization algorithm (CMA) is developed. Numerical simulations are provided to verify the effectiveness and superiority of the proposed LPI-CBORA strategy.