A power allocation strategy for moving target in cognitive FDA-MIMO radar

Nowadays, electromagnetic environment is becoming more and more complex and brings more challenges to radar system. In this paper, we establish a cognitive FDA-MIMO radar framework, which is allowed to control the transmitting element power allocation. Because FDA-MIMO radar contains the frequency offsets across the array, it has ability to adjust the frequency spectrum distribution by power allocation. We apply the cognitive FDA-MIMO radar to moving target tracking in different interference scenarios. The Bayesian Cramer-Rao bound (BCRB) criterion-based power allocation strategy is proposed to adaptively adjust the element power during the whole tracking process. To verify the advantages and effectiveness of the proposed optimization method, we introduce the SINR criterion-based allocation strategy and fixed power allocation strategy compared with the proposed method. Numerical results show that the cognitive FDA-MIMO radar can adaptively adjust the transmitting element frequency to avoid the interference signal frequency for better tracking accuracy. Furthermore, the BCRB criterion-based allocation strategy can obtain superior performance of target tracking compared with the fixed allocation strategy and SINR criterion-based allocation strategy.