Date of Award
Doctor of Philosophy
School of Engineering
Faculty of Computing, Health and Science
Professor Kamal Alameh
Dr Sreten Askraba
Associate Professor Clifton Smith
Over the last decade, substantial research efforts have been dedicated towards the development of advanced laser scanning systems for discrimination in perimeter security, defence, agriculture, transportation, surveying and geosciences. Military forces, in particular, have already started employing laser scanning technologies for projectile guidance, surveillance, satellite and missile tracking; and target discrimination and recognition. However, laser scanning is relatively a new security technology. It has previously been utilized for a wide variety of civil and military applications. Terrestrial laser scanning has found new use as an active optical sensor for indoors and outdoors perimeter security. A laser scanning technique with moving parts was tested in the British Home Office - Police Scientific Development Branch (PSDB) in 2004. It was found that laser scanning has the capability to detect humans in 30m range and vehicles in 80m range with low false alarm rates. However, laser scanning with moving parts is much more sensitive to vibrations than a multi-beam stationary optic approach. Mirror device scanners are slow, bulky and expensive and being inherently mechanical they wear out as a result of acceleration, cause deflection errors and require regular calibration.
Multi-wavelength laser scanning represent a potential evolution from object detection to object identification and classification, where detailed features of objects and materials are discriminated by measuring their reflectance characteristics at specific wavelengths and matching them with their spectral reflectance curves. With the recent advances in the development of high-speed sensors and high-speed data processors, the implementation of multi-wavelength laser scanners for object identification has now become feasible.
A two-wavelength photonic-based sensor for object discrimination has recently been reported, based on the use of an optical cavity for generating a laser spot array and maintaining adequate overlapping between tapped collimated laser beams of different wavelengths over a long optical path. While this approach is capable of discriminating between objects of different colours, its main drawback is the limited number of security-related objects that can be discriminated.
This thesis proposes and demonstrates the concept of a novel photonic based multi-wavelength sensor for object identification and position finding. The sensor employs a laser combination module for input wavelength signal multiplexing and beam overlapping, a custom-made curved optical cavity for multi-beam spot generation through internal beam reflection and transmission and a high-speed imager for scattered reflectance spectral measurements. Experimental results show that five different laser wavelengths, namely 473nm, 532nm, 635nm, 670nm and 785nm, are necessary for discriminating various intruding objects of interest through spectral reflectance and slope measurements. Various objects were selected to demonstrate the proof of concept.
We also demonstrate that the object position (coordinates) is determined using the triangulation method, which is based on the projection of laser spots along determined angles onto intruding objects and the measurement of their reflectance spectra using an image sensor. Experimental results demonstrate the ability of the multi-wavelength spectral reflectance sensor to simultaneously discriminate between different objects and predict their positions over a 6m range with an accuracy exceeding 92%.
A novel optical design is used to provide additional transverse laser beam scanning for the identification of camouflage materials. A camouflage material is chosen to illustrate the discrimination capability of the sensor, which has complex patterns within a single sample, and is successfully detected and discriminated from other objects over a 6m range by scanning the laser beam spots along the transverse direction.
By using more wavelengths at optimised points in the spectrum where different objects show different optical characteristics, better discrimination can be accomplished.
Venkataraayan, K. (2012). Multi-wavelength, multi-beam, photonic based sensor for object discrimination and positioning. https://ro.ecu.edu.au/theses/488