• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.585-589
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• 2009

In this paper, passive direction-finding localization of the emitter using noisy line-of-bearing (LOB) measurements is considered. The performance of the LOB-based emitter localization using linear LSE algorithm is given. The Dependence of the performance on bias of emitter location and sensor trajectory is illustrated using the numerical results.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.121-131
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• 2015

Passive emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. Accurate emitter localization can be expected when utilizing continuous measurable parameters and a appropriate combination of theirs. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to choose a appropriate combination of parameters for a better localization performance. And we propose the passive emitter localization method based on Levenberg-Marquardt algorithm with combined TDOA/FDOA and DOA to achieve better accuracy of emitter localization which is located on the ground and stationary. In addition, we present a method for determining the initial emitter position for LM algorithm's input to avoid the divergence of estimation and local minimum.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.1
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• pp.37-45
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• 2016

In this paper, design and implementation issues for a network-oriented RF emitter localization system with array antenna are discussed. For hardware, the problem of array mismatch and RF/IF channel mismatch are introduced and the calibration schemes for solving those problems are also provided. For software, it is explained how to overcome the drawback of conventional MUltiple Signal Identification and Classification (MUSIC) algorithm in a point of identifying the number of received signals and problems such as Data Association Problem and Ghost Node Problem in regard to multiple emitter localization are presented with some approaches for getting around those problems. Finally, for implementation, a criterion for arranging each of sensors and a requirement for alignment of array antenna' orientation are also given.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.886-893
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• 2010

This paper considers the problem of time difference-of-arrival(TDOA) source localization when the TDOA and angle of arrival(AOA) measurements from an airborne emitter source are subject to ground-platform sensor position. The optimization of sensors' position is a challenging problem and a solution with good localization accuracy has yet to be found. This paper proposes an estimator that can achieve these purposes and provides optimized sensor position for good localization accuracy using the proposed estimator. The developed algorithm and sensor position are then examined under the special case of a single airborne source. The theoretical developments are supported by simulations.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.157-164
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• 2014

The accuracy of instantaneous passive emitter localization varies with sensing platforms and measurable parameters. Appropriate combination of instantaneous measurable parameters have more accurate localization performance than a single parameter based localization in general. Emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to search a appropriate choice of parameters for the better localization performance through the x-y axis CEP (circular error probable) derived form CLRB. In addition, we present the relation of the localization performance and accuracy of measurable parameters.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.4
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• pp.437-445
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• 2009

In this paper, we present the performance of the LOB(line of bearing) - based emitter localization algorithm. The linear LSE(least-squared error) algorithm, nonlinear LSE algorithm and Stansfield algorithm are considered. In addition, we focus on the performance improvement of the weighted estimation compared with the unweighted estimation. Each estimation algorithm is briefly introduced, and the performance of the algorithm is illustrated using the numerical results.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.36-40
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• 2010

In this paper, the well-known LOB-based emitter localization using linear LSE algorithm is numerically implemented and the heuristic guidelines for the parameter values to achieve 1% RMS error are presented. In the simulation, we changed the total observation durations for LOB measurements, time interval between successive LOB measurements and sensor trajectories. The effects of the time interval of LOB measurements, the time duration of the LOB measurements and the angle of flight path arc on the performance are illustrated. The dependence of the performance on the various parameters is investigated and rule-of-thumbs for the parameter values corresponding to 1% RMS error are presented for each simulation condition.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.6
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• pp.727-732
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• 2009

In this paper, the dependence of the Kalman filter-based emitter location algorithm on the initial estimate is investigated. Given all the LOB data, the initial estimate of the emitter location is obtained from the linear LSE algorithm with the former LOB data. Using the initial estimate, the Kalman filter algorithm is applied with the remaining LOB data to update the initial estimate. It is shown that as the number of data used in the calculation of the initial estimate increases, the accuracy of the final estimate is improved and the total computational complexity of obtaining the initial estimate and the final estimate increases. In addition, the dependence of the performance of the Kalman filter algorithm on the predefined constant is illustrated.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.141-147
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• 2017

In this paper, an efficient and robust localization algorithm using Receiver Signal Strength Difference (RSSD) for a non-cooperative RF emitter is given. The proposed algorithm firstly calculate the center point and radius of Apollonius's circles and then estimate the intersection point of the circles based on Time of Arrival concept. And this paper also compares the performance of RSSD localization algorithms such as Non-linear Least Squares and Linearized Least Squares by Lines of Position (LOP) with the proposed algorithm. And some conclusions have been reached regarding the relative accuracy, robustness and computational cost of these algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.88-96
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• 2014

In modern electronic warfare systems, the necessity of a more accurate estimation method based on non-AOA (arrival of angle) measurement, such as TDOA and FDOA, have been increased. The previous researches using single TDOA have been carried out in terms of not only the development of emitter location algorithms but also the enhancement of measurement accuracy. Recently, however, the combined TDOA/FDOA method is of considerable interest because it is able to estimate the velocity vector of a moving emitter and acquire a pair of TDOA and FDOA measurements from a single sensor pair. In this circumstance, it is needed to derive the required FDOA measurement accuracy in order that the TDOA/FDOA combined localization system outperforms the previous single TDOA localization systems. Therefore, we analyze the contribution of FDOA measurement accuracy to emitter location, then propose the criterion based on CRLB (Cramer-Rao lower bound). Simulations are included to examine the validity of the proposed criterion by using the Gauss-Newton algorithm.