8D Parameters Estimation for Bistatic EMVS-MIMO Radar via the nested PARAFAC

TL;DR

This paper introduces a nested PARAFAC algorithm that significantly enhances 8D parameter estimation accuracy for bistatic EMVS-MIMO radar, avoiding extra reconstruction steps and outperforming the original method.

Contribution

A novel nested PARAFAC algorithm is proposed to improve 8D parameter estimation accuracy and efficiency in bistatic EMVS-MIMO radar systems.

Findings

The nested PARAFAC algorithm achieves higher accuracy than the original.

It avoids additional reconstruction processes.

Simulations confirm its effectiveness.

Abstract

In this letter, a novel nested PARAFAC algorithm was proposed to improve the 8D parameters estimation performance for the bistatic EMVS-MIMO radar. Firstly, the outer part PARAFAC algorithm was carried out to estimate the receive spatial response matrix and its first way factor matrix. For the estimated first way factor matrix, a theory is given to rearrange its data into an new matrix, which is the mode-1 unfolding matrix of a three-way tensor. Then, the inner part PARAFAC algorithm was used to estimate the transmit steering vector matrix, the transmit spatial response matrix and the receive steering vector matrix. Thus, the transmit 4D parameters and receive 4D parameters can be accurately located via the abovementioned process. Compared with the original PARAFAC algorithm, the proposed nested PARAFAC algorithm can avoid additional reconstruction process when estimating the transmit/receive spatial response matrix. Moreover, the proposed algorithm can offer a highly-accurate 8D parameters estimaiton than that of the original PARAFAC algorithm. Simulated results verify the effectiveness of the proposed algorithm.