System Concept of WIFI Based Passive Radar
01 Dec 2011-International Journal of Electronics and Telecommunications (Walter de Gruyter GmbH)-Vol. 57, Iss: 4, pp 447-450
TL;DR: In this paper idea of passive radar system based on popular wireless networks commonly named WIFI is presented and it is assumed, that all transmitters operate on the same band frequency and the passive radar receiver has to couple each transmission burst with transmitter position by decoding the physical address of transmitter from captured data stream.
Abstract: In this paper idea of passive radar system based on popular wireless networks commonly named WIFI is presented. In such an networks many transmitters operates in the same channel using multiple access. Wireless networks operating on frequencies 2.4GHz and 5GHz are very common today (IEEE 802.11 a/b/g/n). Classic passive radar determines bistatic distance and velocity by using cross-ambiguity function. To seek target position in XYZ space at least illumination of 3 different transmitters is required. In that paper it was assumed, that all transmitters operate on the same band frequency and the passive radar receiver has to couple each transmission burst with transmitter position by decoding the physical address of transmitter from captured data stream. Having most of the signal sources in our passive radar environment it is possible to detect and to localize objects of interest.
Citations
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TL;DR: A compressed sensing algorithm is proposed to achieve supper resolution and better accuracy, using both the atomic norm and the -norm, to manifest the signal sparsity in the continuous domain.
Abstract: In this paper, we consider the problem of joint delay-Doppler estimation of moving targets in a passive radar that makes use of orthogonal frequency-division multiplexing communication signals. A compressed sensing algorithm is proposed to achieve supper resolution and better accuracy, using both the atomic norm and the $\ell _1$-norm. The atomic norm is used to manifest the signal sparsity in the continuous domain. Unlike previous works that assume the demodulation to be error free, we explicitly introduce the demodulation error signal whose sparsity is imposed by the $\ell _1$-norm. On this basis, the delays and Doppler frequencies are estimated by solving a semidefinite program (SDP) which is convex. We also develop an iterative method for solving this SDP via the alternating direction method of multipliers where each iteration involves closed-form computation. Simulation results are presented to illustrate the high performance of the proposed algorithm.
94 citations
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TL;DR: The results show that the signal-to-noise ratio (SNR) in the RC relative to the SNR in the SC has a significant impact on the passive MLE, and the Cramér-Rao Bound is derived to benchmark the passive estimation performance.
Abstract: We consider the problem of delay and Doppler frequency estimation of a moving target in passive radar using a non-cooperative illuminator of opportunity (IO). The passive radar consists of a reference channel (RC), i.e., an antenna steered to the IO, and a surveillance channel (SC) that collects target echoes. We examine the maximum-likelihood estimator (MLE) for the passive estimation problem by modeling the unknown IO waveform as a deterministic process. Under this condition, the passive MLE is shown to reduce to a cross-correlation and search process using the surveillance signal and a delay-Doppler compensated version of the reference signal. We present two implementations for the passive MLE, including a direct and, respectively, a fast implementation based on a two-dimensional Fast Fourier Transform. In addition, the Cramer-Rao Bound is derived to benchmark the passive estimation performance. The passive MLE is compared via numerical simulation with its active counterpart, which has the exact knowledge of the waveform and uses it for cross-correlation. Our results show that the signal-to-noise ratio (SNR) in the RC relative to the SNR in the SC has a significant impact on the passive MLE. Specifically, if the former is notably higher than the latter (by, e.g., 5 dB), there is a minor difference between the passive and active MLEs for the delay and Doppler estimation; otherwise, the difference is non-negligible and increases with the SNR.
12 citations
Cites background from "System Concept of WIFI Based Passiv..."
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TL;DR: Modifications of the USRP's FPGA configuration and GNU Radio code are proposed for developing six/nine synchronous input channel receiver based on two/tree USRPs respectively and the solution of the problem of the alignment of the data streams being sent from USRP devices via USB to the PC host is proposed.
Abstract: In this paper we present results of research on multichannel receiver using Software Defined Radio technology. This receiver is a part of the experimental FM based passive radar being designed. The hardware platform of the receiver consists of the Universal Software Defined Radio Peripheral devices. In the paper we propose modifications of the USRP's FPGA configuration and GNU Radio code. These modifications allow for developing six/nine synchronous input channel receiver based on two/tree USRPs respectively. Issues of synchronization of separate USRP devices by assuring synchronous sampling were presented. We also propose the solution of the problem of the alignment of the data streams being sent from USRP devices via USB to the PC host.
7 citations
Cites methods from "System Concept of WIFI Based Passiv..."
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Journal Article•
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TL;DR: The algorithms and the results of the experiment for the multistatic passive radar based on the WIFI signal, which detected a Cessna C208 airplane based on low power signal from WifI network nodes, which were acting as non-cooperative illuminators of opportunity.
Abstract: This paper presents the theory and experimental result of passive radar using WIFI transmitters as illuminators of opportunity. As a result of experiments conducted on 17th August 2013 at airfield Chrcynno a Cessna C208 airplane was detected using multistatic passive radar system based on low power signal from WIFI network nodes, which were acting as non-cooperative illuminators of opportunity. In the experiment the 3 wireless access points (AP) were communicating with each other and illuminating the radar scene (airfield). The direct reference and reflected (surveillance) signals have been acquired and processed using specially developed algorithm presented in the paper. After signal processing using Passive Coherent Location methods the target has been detected. This paper describes in details the algorithms and the results of the experiment for the multistatic passive radar based on the WIFI signal.
6 citations
Cites background from "System Concept of WIFI Based Passiv..."
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TL;DR: The results of a dedicated acquisition campaign show that both the detection capability and the localization accuracy progressively degrade as the BI increases due to both the reduction of the received beacons and to the intrinsic undersampling of the target motion.
Abstract: The capability of WiFi-based passive radar to detect, track and profile human targets in both indoor and outdoor environment has been widely demonstrated This paper investigates the impact of the Beacon Interval (BI) on the passive radar performance The results of a dedicated acquisition campaign show that both the detection capability and the localization accuracy progressively degrade as the BI increases due to both the reduction of the received beacons and to the intrinsic undersampling of the target motion Limit values are suggested for practical applications
5 citations
References
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Proceedings Article•
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01 Jan 2009
TL;DR: This paper addresses the real-time localization of transceiver-free targets is addressed by means of learning by example methodology that exploits the received signal strength indicator available at the nodes of a wireless sensor network as input data.
Abstract: The increasing demand in homeland security speeds up the development of innovative and non-invasive systems to localize and track moving objects in complex environments. In this paper the real-time localization of transceiver-free targets is addressed by means of learning by example methodology that exploits the received signal strength indicator available at the nodes of a wireless sensor network as input data. This approach uses neither dedicated sensors nor active devices put on the target to localize both idle and moving objects. The definition of a customized classifier during an offline training procedure enables the real-time generation of a probability map of presence by processing the output of the support vector machine. Some selected experimental results validate the effectiveness of the proposed methodology applied in real scenarios.
4 citations
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