Cognitive Conformal Subaperturing FDA-MIMO Radar for Power Allocation Strategy

Recently, due to its flexible element configuration and more diverse signal processing methods, the conformal array radar has begun to attract wider attention than the conventional array radar. During development of the jamming equipment, the electromagnetic environment becomes more complex, which brings more challenges to the radar system. To overcome the variable interference environment's negative influence on moving target tracking, we propose two adaptive power allocation methods based on two criteria to improve the target tracking accuracy. First, we build the data model of the conformal subaperturing frequency diverse array with multi-input and multi-output radar and the interference signal. Moreover, the Bayesian Cramer–Rao bound (BCRB) and the signal-to-interference-plus-noise ratio (SINR) are derived and taken as the objective functions in proposed optimization problems. Based on this, we build two different power allocation optimization problems under BCRB minimization criterion and SINR maximization criterion, respectively, and two different power constraints are considered. Finally, simulation results verify the effectiveness of the proposed adaptive power allocation methods. The power allocation strategies under two criteria can obtain better tracking accuracy compared with uniform allocation, and the tracking accuracy of the adaptive power allocation method can be influenced by different power constraint conditions.