Use this URL to cite or link to this record in EThOS:
Title: Detection of concealed weapons using acoustic waves
Author: Vadakkel, George Abraham
ISNI:       0000 0004 2740 5198
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2013
Availability of Full Text:
Access from EThOS:
Access from Institution:
Existing weapon detection systems such as metal detectors and X-ray baggage scanners have many drawbacks. While metal detectors can only detect metallic objects, X-ray scanners are unsafe for use on passengers. Also, these systems can only scan people within a short range. These limitations of detecting potentially harmful objects have led to tragic events such as the 9/11 attack on the world trade centre and the 2008 terrorist attack in Mumbai. Development of more advanced security systems would help in curbing such terrorist attacks. These systems could also be used to help security officials in tackling knife and gun related crimes in the streets. The aim of this research is to develop a concealed weapon detection system using acoustic waves. Ideally, the system would have large standoff distance, should be cost-effective and easy to manufacture and would be able to detect both metal and non-metallic weapons. Different techniques such as acoustic signature, resonance acoustic spectroscopy and acoustic imaging were analysed. Acoustic signature techniques identify the target by comparing the acoustic waves reflected by the target to a database of previously recorded acoustic reflections. Resonance acoustic spectroscopy was used on the data acquired using both experimental measurements and Finite Element simulations. A series of resonant frequencies from the acoustic waves reflected by the concealed target were extracted using this technique. This series of resonant frequencies that are unique to the target were used to identify the target. Acoustic camera was used to experimentally record the acoustic reflection from different targets. This was then used to develop images of concealed targets. These tests were performed using commercially available array speaker systems. The probability of improving these results using a better designed ultrasonic or acoustic array speaker system was analysed. This was done by changing different array design parameters and obtaining a highly focused acoustic beam. The results from the experimental tests and Finite Element simulations proved the possibility of using acoustic waves for concealed weapon detection. In the acoustic signature measurements, the frequency spectra of the reflected acoustic waves were shown to be different for different targets. The results from resonance acoustic spectroscopy showed structural resonant frequencies in the frequency spectra that corresponded to the natural frequency of the target. Using acoustic camera kit the image of the concealed target was identified. The array results showed the formation of focused beams for different array configurations. The results showed the formation of grating lobes and side lobes when the inter-element gap became larger than the wavelength of sound waves at the excitation frequency. Finally, a program using neural network was developed to demonstrate how the natural frequencies from the target could be used to identify them. This research work provides a proof of concept of different acoustic wave-based detection and imaging techniques. It has shown the possibility of detecting concealed targets at standoff distances. Using parametric arrays highly focused acoustic or ultrasonic beams could be generated which could be focused on a person suspected of carrying a weapon in a crowded environment. The sound waves reflected back could be analysed using the resonance acoustic spectroscopic technique or one could use the acoustic camera to generate images of targets in real-time. The use of acoustic waves would also help in keeping the cost and complexity of the equipment to a minimum. It also ensures that the public is not exposed to any harmful radiation. The techniques described in this thesis would significantly support the development of a commercially viable, robust acoustic waves based concealed weapon detection system.
Supervisor: Oyadiji, Sunday Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Acoustic ; Concealed weapon detection