Investigation of late time response analysis for detection of multiple concealed objects

Hutchinson, Simon; Fernando, Michael; Andrews, David; Harmer, Stuart; Bowring, Nicholas

doi:10.1117/12.2028378

Cited by 4 publications

(4 citation statements)

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“…This work continues the investigation into coherent full polarimetric radar techniques to maximise acquired information content from scenarios where spatial information content is fundamentally limited due to the effects of effects [1]. In a stand-off security screening scenario millimetre wave techniques have the advantage of being able to penetrate clothing and potential to detect concealed weapons such as person born improvised explosive devices (PBIED) and knives both of metallic or ceramic construction [2], [3], [4], [5], [6], [7]. Target detection using circular polarisation has been trialled [8] and full polarimetry for security screening was initially investigated in [9], [10] using a pseudo monostatic (transmitter and receiver co-located).…”

Section: Introductionmentioning

confidence: 94%

Experimental determination and simulations of the Huynen target parameters for full polarimetric millimetre wave concealed weapon recognition

Blackhurst

Salmon

Southgate³

2018

Millimetre Wave and Terahertz Sensors and Technology XI

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The Huynen polarisation fork as a representation of the full polarimetric radar signature represents a unique and natural description of a target. This paper investigates the use of full polarimetric radar operating over the band 18-26 GHz to measure the Huynen target parameters of size, orientation, helicity, skip angle and fork angle from a range of canonical polarimetric radar targets and classic concealed weapon surrogates. Measurement will determine how accurately the Huynen target parameters represent the geometries of the canonical targets and surrogate weapons such as concealed metal and ceramic guns, shrapnel and plane sheet dielectrics. Target backgrounds will be large area absorbers and the human body to enable assessment of the capability for stand-off concealed weapons detection. The system used for the measurement comprises a dual channel vector network analyser, a Turnstile orthomode transducer (OMT) and a conical horn antenna. The OMT has an isolation better than-35 dB between orthogonal polarisations. This system measures and calibrates the Sinclair matrices of targets, from which the Huynen target parameters are derived. A simple model of targets based on the original work in Huynen thesis back in 1970 will be presented, enabling comparison between measured and simulated Huynen target parameters to be made. Conclusions are that experimental measurements of the Huynen target parameters of canonical and surrogate targets agree well with the basic theory of the technique and simple model simulations.

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Section: Introductionmentioning

confidence: 94%

Experimental determination and simulations of the Huynen target parameters for full polarimetric millimetre wave concealed weapon recognition

Blackhurst

Salmon

Southgate³

2018

Millimetre Wave and Terahertz Sensors and Technology XI

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“…This allows for the resolution of the signal to be improved both in the time and frequency domains dependent on whether the low frequency or high frequency parts of the signal are being analysed. Time frequency analysis has proved useful in discrimination of multiple objects in range and has shown some potential for separation of threat objects obscured by a larger complex object (Hutchinson, et al, 2013) (Atiah & Bowring, 2013) 3.2. Signal Convolution One of the major problems encountered with radar signal processing is the convolution of the antenna response with the useful data.…”

Section: Fourier and Wavelet Analysismentioning

confidence: 99%

“…Current radar systems that use LTR are large, incapable of detecting small-concealed objects within the urban environment and use power levels far too great to be safely applied in personnel screening. This work will build on that discussed in (Hutchinson, et al, 2013)to analyse the effectiveness of the CLEAN deconvolution method (Taylor, et al, 2014) (Hogbom, 1976)) in improving the capabilities of the LTR method for CTD.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the CLEAN deconvolution method for use with Late Time Response analysis of multiple objects

et al. 2014

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This paper investigates the application of the CLEAN non-linear deconvolution method to Late Time Response (LTR) analysis for detecting multiple objects in Concealed Threat Detection (CTD). When an Ultra-Wide Band (UWB) frequency radar signal is used to illuminate a conductive target, surface currents are induced upon the object which in turn give rise to LTR signals. These signals are re-radiated from the target and the results from a number of targets are presented.The experiment was performed using double ridged horn antenna in a pseudo-monostatic arrangement. A Vector network analyser (VNA) has been used to provide the UWB Frequency Modulated Continuous Wave (FMCW) radar signal. The distance between the transmitting antenna and the target objects has been kept at 1 metre for all the experiments performed and the power level at the VNA was set to 0dBm. The targets in the experimental setup are suspended in air in a laboratory environment.Matlab has been used in post processing to perform linear and non-linear deconvolution of the signal. The Wiener filter, Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT) are used to process the return signals and extract the LTR features from the noise clutter. A Generalized Pencil-of-Function (GPOF) method was then used to extract the complex poles of the signal. Artificial Neural Networks (ANN) and Linear Discriminant Analysis (LDA) have been used to classify the data.

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“…Most current radar based algorithms for concealed object classification use simulated data which are free of clutter and generally only contain simple noise sources (such as additive white gaussian noise) [7], [8]. As such, the majority of research on experimental radar signal classification problems for concealed object detection on humans are done in anechoic chambers and are focused on noise removal methods [7], [9], [10]. False positives from prostheses or medical implants such as pacemakers are also of concern for these systems.…”

Section: A Radar Based Concealed Object Detection For Security and Ac...mentioning

confidence: 99%

Generative Adversarial Network for Radar Signal Synthesis

Truong

Yanushkevich

2019

2019 International Joint Conference on Neural Networks (IJCNN)

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A major obstacle in radar based methods for concealed object detection on humans and seamless integration into security and access control system is the difficulty in collecting high quality radar signal data. Generative adversarial networks (GAN) have shown promise in data generation application in the fields of image and audio processing. As such, this paper proposes the design of a GAN for application in radar signal generation. Data collected using the Finite-Difference Time-Domain (FDTD) method on three concealed object classes (no object, large object, and small object) were used as training data to train a GAN to generate radar signal samples for each class. The proposed GAN generated radar signal data which was indistinguishable from the training data by qualitative human observers.

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Investigation of late time response analysis for detection of multiple concealed objects

Cited by 4 publications

References 0 publications

Experimental determination and simulations of the Huynen target parameters for full polarimetric millimetre wave concealed weapon recognition

Experimental determination and simulations of the Huynen target parameters for full polarimetric millimetre wave concealed weapon recognition

Investigation of the CLEAN deconvolution method for use with Late Time Response analysis of multiple objects

Generative Adversarial Network for Radar Signal Synthesis

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