DOA–DOD Estimation for Bistatic MIMO Radar: Entropy-Based Tight Closed-Form Lower Bound

The performance analysis and evaluation criteria of parameter estimation in bistatic multiple-input multiple-output (MIMO) radar are critical. Current approaches primarily rely on Bayesian bounds as performance benchmarks, but their computation involves high-dimensional integration or test-point optimization, increasing complexity. Additionally, closed-form expressions lack explicit characterization of system parameter influences on estimation performance. This work presents an information entropy theory-based framework for evaluating joint direction-of arrival (DOA) and direction-of-departure (DOD) estimation errors in bistatic MIMO radar. By constructing a normalized posterior differential entropy (DE) model across signal-to-noise ratio (SNR) regimes, closed-form entropy error bound (EEB) for joint estimation is derived. The model quantifies relationships between estimation accuracy and key system parameters, including antenna counts, snapshot numbers, and array aperture width. Simulations confirm EEB convergence to Cram´ er-Rao bound (CRB) at high SNR regime and the a priori bound (APB) at low SNR, establishing a unified performance benchmark. Results offer theoretical criteria for optimizing radar array configurations.