This project investigates a laser radar system. The system is based on the principles of time-correlated single photon counting, and by measuring the times-of-flight of reflected photons it can find range profiles and perform three-dimensional imaging of scenes. Because of the photon counting technique the resolution and precision that the system can achieve is very high compared to analog systems. These properties make the system interesting for many military applications. For example, the system can be used to interrogate non-cooperative targets at a safe distance in order to gather intelligence. However, signal processing is needed in order to extract the information from the data acquired by the system. This project focuses on the analysis of different signal processing methods.The Wiener filter and the Richardson-Lucy algorithm are used to deconvolve the data acquired by the photon counting system. In order to find the positions of potential targets different approaches of non-linear least squares methods are tested, as well as a more unconventional method called ESPRIT…
Contents
Introduction
1.1 Background!
1.2 Project outline
1.2.1 Purpose
1.2.2 Previous work
2 Theory
2.1 Time-correlated single photon counting
2.1.1 General principle
2.1.2 Time jitter
2.2 Deconvolution
2.2.1 Wiener filter
2.2.2 Richardson-Lucy algorithm
2.3 Detection!
2.3.1 ESPRIT!
2.3.2 Non-linear least squares
3 Experimental methods!
3.1 The TCSPC system!
3.2 Measurements!
Implementation of signal processing methods!
4.1 Signal processing methods!
4.1.1 Model
4.1.2 Wiener filter
4.1.3 Richardson-Lucy algorithm
4.1.4 ESPRIT
4.1.5 Non-linear least squares
4.2 Image processing
4.2.1 Segmentation
4.2.2 Plane fitting
4.2.3 Cones
5 Results
5.1 One-dimensional results
5.1.1 Deconvolution
5.1.2 Detection
5.2 Three-dimensional results
5.2.1 Plane fitting
5.2.2 Cones
6 Conclusions
6.1 Methods
6.1.1 Wiener filter
6.1.2 ESPRIT
6.1.3 Non-linear least squares
6.1.4 Comparison
6.2 Possible improvements
References
Author: Neimert-Andersson, Thomas
Source: Uppsala University Library
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