On Passive Emitter Tracking in Sensor Networks

Kaune, Regina; Mušicki, D.; Koch, Wolfgang

doi:10.5772/9968

Cited by 10 publications

(13 citation statements)

References 13 publications

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“…6 Future work 1. To remind the reader, the TALA implementation herein requires that three heuristic parameters be set, these being (i): Step 1 Step 3…”

Section: Discussionmentioning

confidence: 99%

“…Let z(i, j) denote the j-th measurement generated by sensor i. It is assumed that target-generated measurements are corrupted by additive Gaussian noise 1 . Hence, for a target located at coordinates X ∈ R 3 , each target-generated measurement at sensor i is given as follows:…”

Section: Step 1: Determine Initial Candidate Locationsmentioning

confidence: 99%

“…see [1] and references therein). Typical applications include detection and localisation of weapon firing events [2,3] and localisation in wireless communication systems [4,5], non-line-ofsight (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Novel maximum likelihood approach for passive detection and localisation of multiple emitters

Hernandez¹

2017

EURASIP J. Adv. Signal Process.

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In this paper, a novel target acquisition and localisation algorithm (TALA) is introduced that offers a capability for detecting and localising multiple targets using the intermittent "signals-of-opportunity" (e.g. acoustic impulses or radio frequency transmissions) they generate. The TALA is a batch estimator that addresses the complex multi-sensor/multi-target data association problem in order to estimate the locations of an unknown number of targets. The TALA is unique in that it does not require measurements to be of a specific type, and can be implemented for systems composed of either homogeneous or heterogeneous sensors. The performance of the TALA is demonstrated in simulated scenarios with a network of 20 sensors and up to 10 targets. The sensors generate angle-of-arrival (AOA), time-of-arrival (TOA), or hybrid AOA/TOA measurements. It is shown that the TALA is able to successfully detect 83-99% of the targets, with a negligible number of false targets declared. Furthermore, the localisation errors of the TALA are typically within 10% of the errors generated by a "genie" algorithm that is given the correct measurement-to-target associations. The TALA also performs well in comparison with an optimistic Cramér-Rao lower bound, with typical differences in performance of 10-20%, and differences in performance of 40-50% in the most difficult scenarios considered. The computational expense of the TALA is also controllable, which allows the TALA to maintain computational feasibility even in the most challenging scenarios considered. This allows the approach to be implemented in time-critical scenarios, such as in the localisation of artillery firing events. It is concluded that the TALA provides a powerful situational awareness aid for passive surveillance operations.

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“…6 Future work 1. To remind the reader, the TALA implementation herein requires that three heuristic parameters be set, these being (i): Step 1 Step 3…”

Section: Discussionmentioning

confidence: 99%

Section: Step 1: Determine Initial Candidate Locationsmentioning

confidence: 99%

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Novel maximum likelihood approach for passive detection and localisation of multiple emitters

Hernandez¹

2017

EURASIP J. Adv. Signal Process.

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“…The detailed analysis of achievable positioning accuracy of TDOA‐based positioning systems is given in Ref. .…”

Section: Introductionmentioning

confidence: 99%

A novel power efficient asynchronous time difference of arrival indoor localization system using CC1101 radio transceivers

Nawaz

Bozkurt

Tekin

2017

Micro & Optical Tech Letters

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results shown in , and 8, in spite of the power amplifier, we obtain a proper S 22 characteristic.The power amplifier is also measured using an IEEE 802.11n WLAN signal (OFDM 64-QAM, 20 MHz bandwidth, and 9.6 dB PAPR). Figure 12 shows the measured gain and PAE with a 2.45-GHz IEEE 802.11n WLAN signal. The power amplifier achieved 7.0% PAE at a linear output power of 21.28 dBm and 26.6 dB power gain. As shown in Figure 13, the maximum linear output power of 21.28 dBm is obtained with 3.8% EVM, which meets the IEEE 802.11n MCS 7 standard. CONCLUSIONIn this work, we design a linear CMOS power amplifier for IEEE 802.11n WLAN applications. We first identify a suitable output transformer structure for a linear CMOS power amplifier. From the results, the driver and power stage of the power amplifier are located outside of the output transformer to mitigate the stability issues. Next, we provide the design procedure of the output matching network to minimize the output return loss. The measured maximum linear output power is 21.28 dBm, while the measured EVM for the IEEE 802.11n input signal is 23.8%. The power amplifier achieved 212.3 dB output return loss. From the measured results, we confirm the feasibility of the proposed linear CMOS power amplifier.ABSTRACT: This paper presents a novel 434MHz asynchronous time difference of arrival (A-TDOA) Indoor Localization System (ILS) using

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“…In order to improve the performance of location estimation, the combination methods employing more than two different estimations are largely used rather than just one. Among those, combining TDOA and FDOA is popularly used because of its relatively high performance and simple implementation [1,2]. The combined TDOA and FDOA estimations are obtained by using the cross ambiguity function (CAF) and this can be easily accomplished by the discrete Fourier transform to the CAF [3].…”

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confidence: 99%

Evaluation of performance enhancement on CRLB of CAF under multiple emitters

Lee

Yang

et al. 2016

Electron. lett.

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A method of enhancing performance is described on the Cramer-Rao lower bound (CRLB) of time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements under multiple emitters. The TDOA and FDOA measurements between two receivers can be simultaneously estimated by using the cross ambiguity function (CAF). However, in the case of multiple emitters, these measurements are contaminated by the inter-symbol interferences (ISIs) which deteriorate the estimation quality. Therefore, it is required to reduce the effect of ISIs for enhancing the performance prior to calculating CAF. For separating the interference signals from the desired signal, we select the angle of arrival estimation algorithm with multiple array antennas. The performance of the estimator can be expressed as CRLB and the separation probability is calculated by employing the locally most powerful test. From the numerical evaluation results, it was observed that the performance could be significantly improved especially for the situation under heavy ISIs.

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On Passive Emitter Tracking in Sensor Networks

Cited by 10 publications

References 13 publications

Novel maximum likelihood approach for passive detection and localisation of multiple emitters

Novel maximum likelihood approach for passive detection and localisation of multiple emitters

A novel power efficient asynchronous time difference of arrival indoor localization system using CC1101 radio transceivers

Evaluation of performance enhancement on CRLB of CAF under multiple emitters

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