Signal Processing Algorithms for Target Parameter Estimation in a Dual-Function Radar Communication System

Abstract

In next-generation technologies, the demand for higher performance in fields such as radar and communications is driving the use of higher frequencies, leading to spectrum congestion. A promising solution to this challenge is the Dual-Function Radar and Communication (DFRC) system, which integrates both radar and communication systems onto a single platform, sharing resources like power, bandwidth, and antennas. One of the key performance metrics in DFRC systems is the accurate estimation of target parameters, such as Direction of Arrival (DOA), range, and velocity. In this thesis, we explore various signal processing algorithms for target parameter estimation.

In the first part of the thesis, we focus on the individual estimation of the target parameters in a multiple input multiple output (MIMO) DFRC systems using Orthogonal Frequency Division Multiplexing (OFDM) as the waveform. Initially, the target DOA estimation using the traditional Fourier Transform method is improved by transmitting a novel waveform that exploits a particular structure of the transmitted signal, which classifies targets into angular zones. As a next step, high-resolution methods such as Capon and subspace methods are made applicable to estimate the target parameters, such as the range and the velocity of the targets, by designing a novel waveform. An alternate way based on the Least squares (LS)/Total LS methods to estimate the target parameters using the conventional OFDM waveform is also investigated.

In the second part of the thesis, we focus on the different combinations of the proposed methods for the estimation of all target parameters. We examine how these methods can be integrated, the types of waveforms, and their impact on the performance metrics of the communication system. To evaluate the proposed methods, we compare them against a benchmark known as the Modified Cramer-Rao Bound.

As an extension, we investigate joint target parameter estimation using Differential Evolution, a genetic algorithm. Additionally, we develop a system model that incorporates index modulation in a MIMO-OFDM DFRC setup, where only a few sub-carriers and antennas are active during the transmission. To optimize radar performance, we propose an approach for selecting the indices of active sub-carriers and antennas using the Pareto front technique.