Noncoherent approach to through-the-wall radar localization
01 Oct 2006-IEEE Transactions on Aerospace and Electronic Systems (IEEE)-Vol. 42, Iss: 4, pp 1405-1419
TL;DR: A noncoherent through-the-wall radar system approach, based on stepped-frequency signal synthesis and trilateration technique, is presented and shows that the radar is able to detect and locate multiple targets behind walls.
Abstract: A noncoherent through-the-wall radar system approach, based on stepped-frequency signal synthesis and trilateration technique, is presented. This approach involves multiple independent monostatic radar units and as such, provides flexibility in positioning the units with various standoff distances and inter-element spacing. The performance of the proposed noncoherent localization system was demonstrated using simulated and real data. The results show that the radar is able to detect and locate multiple targets behind walls
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TL;DR: It is shown that the wall reflections can be effectively reduced by spatial preprocessing prior to beamforming, producing similar imaging results to those achieved when a background scene without the target is available.
Abstract: Radio-frequency imaging of targets behind walls is of value in several civilian and defense applications. Wall reflections are often stronger than target reflections, and they tend to persist over a long duration of time. Therefore, weak and close by targets behind walls become obscured and invisible in the image. In this paper, we apply spatial filters across the antenna array to remove, or at least significantly mitigate, the spatial zero-frequency and low-frequency components which correspond to wall reflections. Unmasking the behind-the-wall targets via the application of spatial filters recognizes the fact that the wall electromagnetic (EM) responses do not significantly differ when viewed by the different antennas along the axis of a real or synthesized array aperture which is parallel to the wall. The proposed approach is tested with experimental data using solid wall, multilayered wall, and cinder block wall. It is shown that the wall reflections can be effectively reduced by spatial preprocessing prior to beamforming, producing similar imaging results to those achieved when a background scene without the target is available.
222 citations
Cites methods from "Noncoherent approach to through-the..."
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TL;DR: Analysis shows that both methods reduce the bias considerably and achieve the CRLB performance for distant source when the noise is Gaussian and small and the BiasRed method is able to lower the bias to the same level as the Maximum Likelihood Estimator.
Abstract: This paper proposes two methods to reduce the bias of the well-known algebraic explicit solution (Chan and Ho, "A simple and efficient estimator for hyperbolic location," IEEE Trans. Signal Process., vol. 42, pp. 1905-1915, Aug. 1994) for source localization using TDOA. Bias of a source location estimate is significant when the measurement noise is large and the geolocation geometry is poor. Bias also dominates performance when multiple times of independent measurements are available such as in UWB localization or in target tracking. The paper starts by deriving the bias of the source location estimate from Chan and Ho. The bias is found to be considerably larger than that of the Maximum Likelihood Estimator. Two methods, called BiasSub and BiasRed, are developed to reduce the bias. The BiasSub method subtracts the expected bias from the solution of Chan and Ho's work, where the expected bias is approximated by the theoretical bias using the estimated source location and noisy data measurements. The BiasRed method augments the equation error formulation and imposes a constraint to improve the source location estimate. The BiasSub method requires the exact knowledge of the noise covariance matrix and BiasRed only needs the structure of it. Analysis shows that both methods reduce the bias considerably and achieve the CRLB performance for distant source when the noise is Gaussian and small. The BiasSub method can nearly eliminate the bias and the BiasRed method is able to lower the bias to the same level as the Maximum Likelihood Estimator. The BiasRed method is extended for TDOA and FDOA positioning. Simulations corroborate the performance of the proposed methods.
221 citations
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TL;DR: The novel idea of hypothesized source locations in the algorithm development is introduced to enable the formulation of psuedolinear equations, thereby leading to the establishment of closed-form solution for source location estimates.
Abstract: This paper considers the problem of time difference-of-arrival (TDOA) source localization when the TDOA measurements from multiple disjoint sources are subject to the same sensor position displacements from the available sensor positions. This is a challenging problem and closed-form solution with good localization accuracy has yet to be found. This paper proposes an estimator that can achieve this purpose. The proposed algorithm jointly estimates the unknown source and sensor positions to take the advantage that the TDOAs from different sources have the same sensor position displacements. The joint estimation is a highly nonlinear problem due to the coupling of source and sensor positions in the measurement equations. We introduce the novel idea of hypothesized source locations in the algorithm development to enable the formulation of psuedolinear equations, thereby leading to the establishment of closed-form solution for source location estimates. Besides the advantage of closed-form, the newly developed algorithm is shown analytically, under the condition that the TDOA measurement noise and the sensor position errors are sufficiently small, to reach the CRLB accuracy. For clarity, the localization of two disjoint sources is used in the algorithm development. The developed algorithm is then examined under the special case of a single source and extended to the more general case of more than two unknown sources. The theoretical developments are supported by simulations.
186 citations
Cites background from "Noncoherent approach to through-the..."
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TL;DR: An autofocusing technique, based on higher order statistics, is presented which corrects for errors under unknown walls and provides high-quality focused images with target locations in close proximity to true target positions.
Abstract: The quality and reliability of through-the-wall radar imagery is governed, among other things, by the knowledge of the wall characteristics. Ambiguities in wall characteristics smear and blur the image, and also shift the imaged target positions. An autofocusing technique, based on higher order statistics, is presented which corrects for errors under unknown walls. Simulation results show that the proposed technique provides high-quality focused images with target locations in close proximity to true target positions.
153 citations
References
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TL;DR: An overview of wireless location challenges and techniques with a special focus on network-based technologies and applications is provided.
Abstract: Wireless location refers to the geographic coordinates of a mobile subscriber in cellular or wireless local area network (WLAN) environments. Wireless location finding has emerged as an essential public safety feature of cellular systems in response to an order issued by the Federal Communications Commission (FCC) in 1996. The FCC mandate aims to solve a serious public safety problem caused by the fact that, at present, a large proportion of all 911 calls originate from mobile phones, the location of which cannot be determined with the existing technology. However, many difficulties intrinsic to the wireless environment make meeting the FCC objective challenging. These challenges include channel fading, low signal-to-noise ratios (SNRs), multiuser interference, and multipath conditions. In addition to emergency services, there are many other applications for wireless location technology, including monitoring and tracking for security reasons, location sensitive billing, fraud protection, asset tracking, fleet management, intelligent transportation systems, mobile yellow pages, and even cellular system design and management. This article provides an overview of wireless location challenges and techniques with a special focus on network-based technologies and applications.
1,260 citations
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TL;DR: Written for researchers and engineers working in the field, Radar Systems Analysis and Design Using MATLAB provides fundamental radar principles, advanced topics, and rigorous but easy-to-follow mathematical derivations.
Abstract: From the Publisher:
Written for researchers and engineers working in the field, Radar Systems Analysis and Design Using MATLAB provides fundamental radar principles, advanced topics, and rigorous but easy-to-follow mathematical derivations.
875 citations
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01 Jan 1986
TL;DR: The solution of Large-scale Programming Problems: Generalized Linear Programming and Decomposition Techniques Dynamic Programming Optimization in Infinite Dimension and Applications is presented.
Abstract: Preface Foreword Notation Fundamental Concepts Linear Programming One-dimensional Optimization Nonlinear, Unconstrained Optimization Nonlinear Optimization with Constraints Nonlinear Constrained Optimization Integer Programming Solution of Large-scale Programming Problems: Generalized Linear Programming and Decomposition Techniques Dynamic Programming Optimization in Infinite Dimension and Applications References Appendices Index.
559 citations
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TL;DR: The measurement and simulation methods presented in this paper can be used to establish empirical performance bounds for real implementation of super-resolution indoor geolocation systems.
Abstract: This paper presents an in-depth investigation of frequency-domain super-resolution time-of-arrival (TOA) estimation with diversity techniques for indoor geolocation applications. A methodology for performance evaluation of super-resolution techniques based on the measurements of indoor radio propagation channels is presented. The performance of super-resolution techniques is compared with the performance of conventional TOA estimation techniques. The effects of diversity techniques on the performance of super-resolution techniques are evaluated. The measurement and simulation methods presented in this paper can be used to establish empirical performance bounds for real implementation of super-resolution indoor geolocation systems.
542 citations
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TL;DR: An overview of challenging issues for the collaborative processing of wideband acoustic and seismic signals for source localization and beamforming in an energy-constrained distributed sensor network.
Abstract: Distributed sensor networks have been proposed for a wide range of applications. The main purpose of a sensor network is to monitor an area, including detecting, identifying, localizing, and tracking one or more objects of interest. These networks may be used by the military in surveillance, reconnaissance, and combat scenarios or around the perimeter of a manufacturing plant for intrusion detection. In other applications such as hearing aids and multimedia, microphone networks are capable of enhancing audio signals under noisy conditions for improved intelligibility, recognition, and cuing for camera aiming. Previous developments in integrated circuit technology have allowed the construction of low-cost miniature sensor nodes with signal processing and wireless communication capabilities. These technological advances not only open up many possibilities but also introduce challenging issues for the collaborative processing of wideband acoustic and seismic signals for source localization and beamforming in an energy-constrained distributed sensor network. The purpose of this article is to provide an overview of these issues.
528 citations