Joint range and velocity estimation for integration of radar and communication based on multi‐symbol OFDM radar pulses

Abstract

Integration of radar and communication (IRC) is conducive to improving hardware resource utilization and spectrum utilization. This paper proposes a joint range and velocity estimation method for IRC based on multi-symbol orthogonal frequency division multiplexing (OFDM) radar pulses. A two-step parameters estimation method is applied, where estimating the signal parameters via rotational invariance technique (ESPRIT) and weighted subspace fitting (WSF) perform rough and fine estimations. We first build a receiving model for integrated signal based on element-wise division. The ESPRIT method is then adopted based on the double Vandermonde structure array manifold for a rough estimation. It has relatively high estimation error but low computational complexity. The WSF method based on alternating projection (AP) algorithm is introduced to make the estimation more precise and reduce its error. It uses the estimation results in the first step and reduces the overall computational cost. Simulation results show that the proposed method reduces the computational complexity while improving the estimation accuracy compared with the WSF method.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Joint range and velocity estimation for orthogonal frequency division multiplexing‐based high‐speed integrated radar and communications system

“…More range velocity points need to be searched to improve the accuracy of the algorithm. However, most of the range velocity points are invalid, and the computational time of these points occupies the majority of that of the algorithm [28]. Therefore, we propose the E‐L two‐step estimation as the solution.…”

Power Resource Allocation Algorithm for Dual-Function Radar–Communication System

“…In recent years, the rapid growth of wireless systems has led to a scarcity of spectrum resources, raising concerns [1]. As the communication system gradually develops to a higher frequency band, it overlaps with the operating frequency band of the radar system, resulting in an increasingly fierce resource scramble between the two, and the research on the integration of radar communication has become a research hotspot [2][3][4][5][6][7][8]. With the deepening of research, dual-function radar-communication (DFRC) system is proposed.…”

基于稀疏重构预处理的otfs雷达通信一体化目标参数估计算法

“…Li SY et al (2022) proposed an integrated system based on spatially spread orthogonal time frequency space (SS-OTFS), designed the angle-of-arrival (AOA) estimation algorithm using the radar sensing matrix structure, and investigated the power allocation problem of the system. The traditional algorithms for the joint estimation of angle and delay, to achieve signal processing, include mainly the multiple signal classification (MUSIC) algorithm (Shi et al, 2019), the weighted subspace fitting (WSF) algorithm (Wang et al, 2021), the ML algorithm (Zhang FQ et al, 2020), and the compressed sensing (CS) algorithm (Zheng and Wang, 2017;Rahman et al, 2020). However, all these methods require complex computational processes such as matrix decomposition, optimization, and search, and have high computational complexity.…”