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Compared with the traditional phased array radar, the co-located multiple-input multiple-output (MIMO) radar is able to transmit orthogonal waveforms to form different illuminating modes, providing a larger freedom degree in radar resource management. In order to implement the effective resource management for the co-located MIMO radar in multi-target tracking, this paper proposes a resource management optimization model, where the system resource consumption and the tracking accuracy requirements are considered comprehensively. An adaptive resource management algorithm for the co-located MIMO radar is obtained based on the proposed model, where the sub-array number, sampling period, transmitting energy, beam direction and working mode are adaptively controlled to realize the time-space resource joint allocation. Simulation results demonstrate the superiority of the proposed algorithm. Furthermore, the co-located MIMO radar using the proposed algorithm can satisfy the predetermined tracking accuracy requirements with less comprehensive cost compared with the phased array radar.

To address the problem of target detection in distributed MIMO radar, three styles of distributed MIMO radar systems are given in this paper. With respect to the geometric distribution relations of distributed MIMO radar, the styles are distributed coherent MIMO radar, random phase MIMO radar, and random amplitude-phase MIMO radar. Next, the square law detector structures of random phase and random amplitude-phase MIMO radar are derived in the paper when there is a low signal-to-noise ratio, and the performance of the two detectors are analyzed as well. Finally, simulation results demonstrate the theoretical analysis of this paper are of guiding significance for the actual engineering.

Only a subset of transmitters and receivers in a distributed Multi-Input Multi-Output (MIMO) radar network is allowed to actively track a target at a particular instance due to the limited time and energy resource of a MIMO radar network. It is therefore desirable to obtain an efficient method to overcome the resource constraints while optimizing the tracking performance. In this study, posterior Cramer-Rao lower bound is used as the performance metric and the selection problem is formulated as a Boolean programming problem aiming at optimizing the worst tracking performance of multiple targets. It is later relaxed to a semidefinite programming and solved by the block coordinate descend method. Numerical results show that proposed method superior to the fixed selection method. In addition, with less computation complexity, the proposed method obtains nearly equivalent performance compared with exhaustive search method.