Distributed computation for direct position determination emitter location

Pourhomayoun, Mohammad; Fowler, Mark L.

doi:10.1109/taes.2014.130005

Cited by 32 publications

(30 citation statements)

References 16 publications

(55 reference statements)

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“…In particular, DPD methods for locating a narrowband radio emitter based on Doppler shift [18,19] and for locating a wideband source using a time delay metric [20][21][22] have been presented. Additionally, DPD estimators using both the Doppler effect and the relative delay have been developed [23][24][25][26]. In the DPD methods mentioned above, several platforms each carrying single-antenna receivers are used for source location; hence, the DOA information of the impinging signals cannot be exploited.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, DPD methods tailored to special signal structures (e.g., orthogonal frequency division multiplexing signals, cyclostationary signals, noncircular signals, and intermittent emissions) have been developed [33][34][35][36][37]. Note that the experimental results in [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] demonstrate that the single-step approach outperforms the two-step method in scenarios with low SNR and/ or relatively few data records.…”

Section: Introductionmentioning

confidence: 99%

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Robust direct position determination methods in the presence of array model errors

Wang

Yin

Liu

et al. 2018

EURASIP J. Adv. Signal Process.

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Direct position determination (DPD) methods are known to have many advantages over the traditional two-step localization method, especially for low signal-to-noise ratios (SNR) and/or short data records. However, similar to conventional direction-of-arrival (DOA) estimation methods, the performance of DPD estimators can be dramatically degraded by inaccuracies in the array model. In this paper, we present robust DPD methods that can mitigate the effects of these uncertainties in the array manifold. The proposed technique is related to the classical auto-calibration procedure under the assumption that prior knowledge of the array response errors is available. Localization is considered for the cases of both unknown and a priori known transmitted signals. The corresponding maximum a posteriori (MAP) estimators for these two cases are formulated, and two alternating minimization algorithms are derived to determine the source location directly from the observed signals. The Cramér-Rao bounds (CRBs) for position estimation are derived for both unknown and known signal waveforms. Simulation results demonstrate that the proposed algorithms are asymptotically efficient and very robust to array model errors.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust direct position determination methods in the presence of array model errors

Wang

Yin

Liu

et al. 2018

EURASIP J. Adv. Signal Process.

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show abstract

“…Specifically, the DPD method for locating a narrowband radio emitter based on a Doppler shift is presented in [ 20 , 21 ], and DPD methods for locating a wideband source based on a time delay metric are proposed in [ 22 , 23 , 24 ]. Furthermore, DPD estimators using both the Doppler frequency and time delay are developed in [ 25 , 26 , 27 , 28 ]. Note that in the DPD methods mentioned above, multiple platforms each equipped with a single-antenna receiver are used for position determination, and as a result, the DOA information of the impinging signals cannot be exploited.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, DPD methods tailored to special signals (e.g., orthogonal frequency division multiplexing signals, cyclostationary signals, and intermittent emissions) are proposed in [ 37 , 38 , 39 ]. It is noteworthy that all experiment results in [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ] demonstrate that the single-step approach outperforms the two-step method for a low signal-to-noise ratio (SNR) and small number of samples. Meanwhile, although this kind of localization method may require more computations and communication bandwidth, novel information technology [ 40 , 41 , 42 ] can be used to overcome these difficulties.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of the Direct Position Determination Method in the Presence of Array Model Errors

Wang

et al. 2017

Sensors

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The direct position determination approach was recently presented as a promising technique for the localization of a transmitting source with accuracy higher than that of the conventional two-step localization method. In this paper, the theoretical performance of a direct position determination estimator proposed by Weiss is examined for situations in which the array model errors are present. Our study starts from a matrix eigen-perturbation result, which expresses the perturbation of eigenvalues as a function of the disturbance added to the Hermitian matrix. The first-order asymptotic expression of the positioning errors is presented, from which an analytical expression for the mean square error of the direct localization is available. Additionally, explicit formulas for computing the probabilities of a successful localization are deduced. Finally, Cramér–Rao bound expressions for the position estimation are derived for two cases: (1) array model errors are absent and (2) array model errors are present. The obtained Cramér-Rao bounds provide insights into the effects of the array model errors on the localization accuracy. Simulation results support and corroborate the theoretical developments made in this paper.

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“…In addition, this kind of method requires a high bandwidth which is generally limited in wireless sensor networks (WSNs) and also may cause a large processing delay [21]. This would have significant impacts on the size, weight, and power (SWaP) requirement of that sensor [22].…”

Section: Introductionmentioning

confidence: 99%

A Moving Source Localization Method for Distributed Passive Sensor Using TDOA and FDOA Measurements

Liu¹,

Zhao²,

Hu³

et al. 2016

International Journal of Antennas and Propagation

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The conventional moving source localization methods are based on centralized sensors. This paper presents a moving source localization method for distributed passive sensors using TDOA and FDOA measurements. The novel method firstly uses the steepest descent algorithm to obtain a proper initial value of source position and velocity. Then, the coarse location estimation is obtained by maximum likelihood estimation (MLE). Finally, more accurate location estimation is achieved by subtracting theoretical bias, which is approximated by the actual bias using the estimated source location and noisy data measurement. Both theoretical analysis and simulations show that the theoretical bias always meets the actual bias when the noise level is small, and the proposed method can reduce the bias effectively while keeping the same root mean square error (RMSE) with the original MLE and Taylor-series method. Meanwhile, it is less sensitive to the initial guess and attains the CRLB under Gaussian TDOA and FDOA noise at a moderate noise level before the thresholding effect occurs.

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Distributed computation for direct position determination emitter location

Cited by 32 publications

References 16 publications

Robust direct position determination methods in the presence of array model errors

Robust direct position determination methods in the presence of array model errors

Performance Analysis of the Direct Position Determination Method in the Presence of Array Model Errors

A Moving Source Localization Method for Distributed Passive Sensor Using TDOA and FDOA Measurements

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