Joint Adaptive Sampling Interval and Power Allocation for Maneuvering Target Tracking in a Multiple Opportunistic Array Radar System. In this paper, a joint adaptive sampling interval and power allocation (JASIPA) scheme based on chanceconstraint programming (CCP) is proposed for maneuvering target tracking (MTT) in a multiple opportunistic array radar (OAR) system. In order to conveniently predict the maneuvering target state of the next sampling instant, the bestfitting Gaussian (BFG) approximation is introduced and used to replace the multimodal prior target probability density function (PDF) at each time step. Since the mean and covariance of the BFG approximation can be computed by a recursive formula, we can utilize an existing Riccatilike recursion to accomplish effective resource allocation. The prior CramerRao lower boundary (prior CRLBlike) is compared with the upper boundary of the desired tracking error range to determine the adaptive sampling interval, and the Bayesian CRLBlike (BCRLBlike) gives a criterion used for measuring power allocation. In addition, considering the randomness of target radar cross section (RCS), we adopt the CCP to package the deterministic resource management model, which minimizes the total transmitted power by effective resource allocation. Lastly, the stochastic simulation is embedded into a genetic algorithm (GA) to produce a hybrid intelligent optimization algorithm (HIOA) to solve the CCP optimization problem. Simulation results show that the global performance of the radar system can be improved effectively by the resource allocation scheme.

Joint Waveform and Receiver Design for CoChannel Hybrid ActivePassive Sensing With Timing Uncertainty We consider a hybrid activepassive radar system that employs a wireless source as a passive illuminator of opportunity (IO) and a cochannel active radar transmitter operating in the same frequency band to seek spectral efficiency. The hybrid system can take advantage of the strengths of passive radar (e.g., energy efficiency, bimultistatic configuration, and spatial diversity) as well as those of active radar (dedicated transmitter, flexible transmit beam steering, waveform optimized for sensing, etc.). To mitigate the mutual interference and locationinduced timing uncertainty between the radar and communication signals, we propose two designs for the joint optimization of the radar waveform and receive filters. The first is a maxmin (MM) criterion that optimizes a worstcase performance metric over a timing uncertainty interval, and the other a weightedsum (WS) criterion that forms a weighted sum of the performance metric at each delay within the delay uncertainty interval. Both design criteria result in nonconvex constrained optimization problems that are solved by sequential convex programming methods. When timing uncertainty vanishes, the two designs become identical and admit a simpler solution. Numerical results are presented to demonstrate the performance of the proposed hybrid schemes in comparison with conventional activeonly and passiveonly radar systems.