Nonlinear Chance Constrained Programming Based Robust Power Allocation Algorithm for Multistatic Radar Systems

Almost all the existing works on power allocation assume that the target Radar Cross Section (RCS) information is known a priori. In order to deal with the uncertainty of the target RCS, a robust power allocation algorithm for MultiStatic Radar Systems (MSRS) is proposed based on Nonlinear Chance Constrained Programming (NCCP), in which the target RCS is modeled as a random variable with unknown distribution. Firstly, the Bayesian Cramer Rao Lower Bound (BCRLB) is derived. Then, the NCCP model is built with the objective of minimizing the total transmit power of MSRS, while the BCRLB outage probability is enforced to be greater than a specified probability. The resulting stochastic optimization issue is solved via Conditional Value at Risk (CVaR) relaxation and Sample Average Approximation (SAA) method. Finally, the validity and robustness of the proposed algorithm are verified with the simulation results.