# Transmit Array Interpolation for DOA Estimation via Tensor Decomposition in 2D MIMO Radar

## TL;DR

This paper introduces a 2D joint transmit array interpolation and tensor-based DOA estimation method for MIMO radar, improving accuracy and SNR by mapping the array to a desired configuration and compensating for interpolation bias.

## Contribution

It proposes a novel tensor-based DOA estimation approach with a closed-form bias correction and CRB analysis for 2D MIMO radar systems.

## Key findings

- Enhanced DOA estimation accuracy demonstrated in simulations
- Bias correction improves estimation reliability
- Performance approaches the derived CRB

## Abstract

In this paper, we propose a two-dimensional (2D) joint transmit array interpolation and beamspace design for planar array mono-static multiple-input-multiple-output (MIMO) radar for direction-of-arrival (DOA) estimation via tensor modeling. Our underlying idea is to map the transmit array to a desired array and suppress the transmit power outside the spatial sector of interest. In doing so, the signal-tonoise ratio is improved at the receive array. Then, we fold the received data along each dimension into a tensorial structure and apply tensor-based methods to obtain DOA estimates. In addition, we derive a close-form expression for DOA estimation bias caused by interpolation errors and argue for using a specially designed look-up table to compensate the bias. The corresponding Cramer-Rao Bound (CRB) is also derived. Simulation results are provided to show the performance of the proposed method and compare its performance to CRB.