Mono-static and Bi-static MIMO radar: targets localisation
File(s)
Final PhD thesis submitted on 13/11/2024 by Nadeem Dar
Author(s)
Dar, Nadeem
Type
Thesis
Abstract
This thesis explores the application of multiple-input multiple-output (MIMO) radar technology for enhanced parameter estimation in both monostatic and bistatic configurations. It leverages the combined power of spatial and waveform diversities, along with basic and extended array manifolds, to achieve superior performance.
It begins with an overview of recent advancements in MIMO radar technology, introducing and exploring core concepts critical for understanding the system's operation. The focus then shifts to a Saab monostatic MIMO experimental radar system. By modelling system blocks from transmitter to receiver, it analyses the performance of classical parameter estimation algorithms and compares these with novel virtual MIMO algorithms, highlighting their potential for improvement.
The thesis proposes innovative subspace-based algorithms designed for bistatic MIMO radar systems. These algorithms utilise fast and slow time coding to achieve waveform diversity and an extended observation space through extended manifolds. This enables accurate target parameter estimation even in environments with significant clutter and noise. The performance of these algorithms is evaluated using root-mean-square error (RMSE) in Monte Carlo simulations.
Furthermore, the thesis examines the theoretical performance limitations of the antenna arrays employed, comparing their performance with a uniform circular array (UCA) to highlight the trade-offs associated with different array geometries.
This thesis introduces novel algorithms and insights that advance MIMO radar parameter estimation, paving the way for improved target localisation in complex scenarios.
It begins with an overview of recent advancements in MIMO radar technology, introducing and exploring core concepts critical for understanding the system's operation. The focus then shifts to a Saab monostatic MIMO experimental radar system. By modelling system blocks from transmitter to receiver, it analyses the performance of classical parameter estimation algorithms and compares these with novel virtual MIMO algorithms, highlighting their potential for improvement.
The thesis proposes innovative subspace-based algorithms designed for bistatic MIMO radar systems. These algorithms utilise fast and slow time coding to achieve waveform diversity and an extended observation space through extended manifolds. This enables accurate target parameter estimation even in environments with significant clutter and noise. The performance of these algorithms is evaluated using root-mean-square error (RMSE) in Monte Carlo simulations.
Furthermore, the thesis examines the theoretical performance limitations of the antenna arrays employed, comparing their performance with a uniform circular array (UCA) to highlight the trade-offs associated with different array geometries.
This thesis introduces novel algorithms and insights that advance MIMO radar parameter estimation, paving the way for improved target localisation in complex scenarios.
Version
Open Access
Date Issued
2024-07-16
Date Awarded
01/12/2024
Advisor
Manikas, Athanassios
Sponsor
Saab Innovation Centre UK (Firm)
Grant Number
EESB P78823
Publisher Department
Electrical and Electronic Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)