Antenna Array Aperture Resource Management of Opportunistic Array Radar for Multiple Target Tracking

• Main Authors: Qinghua Han, Yuanshi Zhang, Zhen Yang, Weijun Long, Zhiheng Liang
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Antenna array aperture resource management; Bayesian Cramér-Rao lower bound (BCRLB); chance-constraint programming (CCP); opportunistic array radar (OAR)
• Online Access: https://ieeexplore.ieee.org/document/9293276/

In this paper, an antenna array aperture resource management scheme of opportunistic array radar (OAR) based on chance-constraint programming (CCP) is proposed for multiple target tracking (MTT). In the multi-target tracking scenario, multiple beams need to be synthesized to illuminate the targets. According to the predicted distance of targets, the OAR can intelligently segment the antenna array aperture, and select the optimal combination of array elements to synthesize the satisfactory beams with the element-level antenna steering. Owing to the unique array arrangement and work mode of opportunistic array, the element number in working modes is uncertain. To represent the uncertainty, a fuzzy CCP model is introduced. The element number in working modes is viewed as a fuzzy variable. The maximum tracking error, which is denoted by Bayesian Cramér-Rao lower bound(BCRLB), of the targets is regarded as the objective function. The fuzzy simulation algorithm is embedded into genetic algorithm (GA) to compose a hybrid intelligent optimization algorithm to solve the CCP problem. The simulation results verify the validity and practicability of the antenna array aperture resource allocation scheme.