Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
167 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Search-free DOA Estimation Method Based on Tensor Decomposition and Polynomial Rooting for Transmit Beamspace MIMO Radar (2010.03296v2)

Published 7 Oct 2020 in cs.IT, eess.SP, and math.IT

Abstract: In order to improve the accuracy and resolution for transmit beamspace multiple-input multiple-output (MIMO) radar, a search-free direction-of-arrival (DOA) estimation method based on tensor decomposition and polynomial rooting is proposed. In the proposed method, a 3-order tensor is firstly designed to model the received signal of MIMO radar on the basis of the multi-linear property. Then, the factor matrix with target DOA information is obtained by the tensor decomposition via alternating least squares (ALS) algorithm, and subsequently the DOA estimation is converted into the independent minimization problem. By exploiting the Vandermonde structure of the transmit steering vector, a polynomial function is constructed to solve the minimization problem via polynomial rooting. The factor matrix contained in the coefficients of the polynomial can be regarded as a block matrix in the generalized sidelobe canceller (GSC), which accordingly forms a unique deep null in the direction of target in the transmit beampattern. The proposed method can obtain the DOA estimation without the requirements of spectrum searching or transmit beamspace matrix design, which is different from the conventional DOA estimation techniques. The effectiveness of the proposed method is verified by the simulations.

Citations (1)

Summary

We haven't generated a summary for this paper yet.