Decentralized direction finding using Lanczos method

The problem of Direction of Arrival (DoA) estimation using partly calibrated arrays composed of multiple identically oriented subarrays is considered. The subarrays are assumed to possess the shift invariance property which is exploited to achieve decentralized search free DoA estimation based on the ESPRIT method. In our previous work, the decentralized power method and the Averaging Consensus (AC) algorithm were used in the subspace estimation. To reduce the communicational cost without compromising the performance, our new algorithm uses the decentralized Lanczos method in combination with the AC algorithm to estimate the signal subspace. We further address the problem of Spurious Eigenvalues (SEVs) that usually arises in the Lanczos method. We propose a scheme to avoid the occurrence of SEVs while keeping the communicational cost low. Simulation results demonstrate that the proposed scheme is able to achieve similar performance as the decentralized power method with substantially reduced communicational cost. Furthermore, our method is able to estimate more DoAs than each subarray can autonomously identify.