In this paper, we propose a joint waveform selection and power allocation (JWSPA) strategy based on chance-con-straint programming (CCP) for manned/unmanned aerial vehicle hybrid swarm (M/UAVHS) tracking a single target. Accordingly, the low probability of intercept (LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section (RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation (ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation, the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound (BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelliūgent algorithms, in which the stochastic simulation is integrated into the genetic algorithm (GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.

ZHANG Yuanshi;PAN Minghai;LONG Weijun;LI Hua;HAN Qinghua

College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;Nanjing Research Institute of Electronics Technology, Nanjing 210039, China;College of Artificial Intelligence,Zaozhuang University, Zaozhuang 277160, China

系统工程与电子技术（英文版）

[1]ZHANG Yuanshi;PAN Minghai;LONG Weijun;LI Hua;HAN Qinghua-.Joint waveform selection and power allocation algorithm in manned/unmanned aerial vehicle hybrid swarm based on chance-constraint programming)[J].系统工程与电子技术（英文版）,2022(03):551-562

JWSPA,UAVHS

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