Adaptive channel selection for DOA estimation in MIMO radar
This work addresses the problem of efficient antenna selection for DOA estimation in radar systems, offering an adaptive method that outperforms existing approaches in simulations.
The paper proposes adaptive antenna selection strategies for DOA estimation in TDM MIMO radar, using one-step ahead predictions of Bayesian MSE via Weiss-Weinstein bounds. Simulations show improved performance compared to policies optimizing other bounds under varying noise levels.
We present adaptive strategies for antenna selection for Direction of Arrival (DoA) estimation of a far-field source using TDM MIMO radar with linear arrays. Our treatment is formulated within a general adaptive sensing framework that uses one-step ahead predictions of the Bayesian MSE using a parametric family of Weiss-Weinstein bounds that depend on previous measurements. We compare in simulations our strategy with adaptive policies that optimize the Bobrovsky- Zakaı bound and the Expected Cramér-Rao bound, and show the performance for different levels of measurement noise.