Emitter Location Estimation Research Articles

Joint Scan Rate and Emitter Location Estimation Algorithm in SBR System Based on AOA and DTOST Measurements

A joint scan rate and emitter location estimation algorithm in scan-based radar (SBR) system based on the angle-of-arrival (AOA) and the difference time of scan time (DTOST) measurements is proposed in this paper. SBR localization is a kind of passive geolocation technique for stationary pulsed radars. To date, a huge number of passive localization techniques using AOA, DTOST or other measurements for SBR have been developed assuming prior knowledge of the scan rate. However, it is usually hard to obtain the accurate scan velocity in most of practical civilian and military applications. In this paper, by using the linear correlation between AOA and DTOST, the maximum likelihood (ML) estimation algorithm based on linear constraints is given to obtain the scan rate of SBR. And the new AOA information after fusion is acquired on this basis. Then the weighted least square (WLS) method is used for SBR localization and the Cramer-Rao lower bound (CRLB) is derived for SBR location estimation. A detailed analysis of scan rate and emitter location estimation process is given and the effectiveness of the proposed localization algorithm is illustrated with computer simulations.

Gauss Hermite H ∞ Filter for UAV Tracking Using LEO Satellites TDOA/FDOA Measurement—Part I

The precision geolocation and target tracking problem has been addressed in this paper using High-Degree Non-linear Filtering based on hybrid Time Difference of Arrival (TDOA), Frequency Difference of Arrival (FDOA) measurements using Low Earth Orbit (LEO) satellite with slant range. In order to update the noise covariance and estimation process at each measurement, the Gauss Hermite H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> Filter based on hybrid TDOA/FDOA geolocation measurements are proposed in this work. Numerous scenarios with the different rotation speed of Radio Frequency (RF) emitter has been considered. Multi LEO satellites have used to estimate and track the location of the unknown Unmanned Aerial Vehicle (UAV) under uncertainties of measurements. The uncertainties of measurements have been considered because the position and velocity of sensors are not fixed, which may affect the emitter location estimation measurements. The Cramer-Rao Lower Bound (CRLB) is used as a metric for measuring and analyzing the performance of the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> /GHKF 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> degree and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> /GHKF 5 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> degree algorithm, as well as compare it with state-of-the-art algorithms. The simulation results of the proposed algorithm indicate that the significant improvement in performance for example, 10% based on TDOA, 40% for FDOA, and 50% on TDOA/FDOA have been achieved.

Noniterative Three-Dimensional Location Estimation Using Azimuth and Elevation Measurements at Multiple Locations

Closed-form expression of three-dimensional emitter location estimation using azimuth and elevation measurements at multiple locations is presented in this paper. The three-dimensional location estimate is obtained from three-dimensional sensor locations and the azimuth and elevation measurements at each sensor location. Since the formulation is not iterative, it is not computationally intensive and does not need initial location estimate. Numerical results are presented to show the validity of the proposed scheme.

Direct Position Determination Sensitivity to NLOS Propagation Effects on Doppler-Shift

In this paper, we consider the Direct Position Determination (DPD) algorithm for Doppler-shift based localization of radio-emitters. The DPD emitter location estimate is the location candidate that maximizes the largest eigenvalue of a location-dependent matrix. The sensitivity to multipath is analyzed by Small Error Analysis, which requires expressions for the derivatives of the largest eigenvalue with respect to the multipath parameters. We consider multipath conditions in which the line-of-sight path is obstructed and the receivers intercept a non-line-of-sight (NLOS) component. We provide compact closed-form expressions for these derivatives. Our theoretical results are corroborated by numerical experiments.

Industrial Trends in Development of Target Mapping Interface for Passive Radar Systems

Passive emitter location systems have a wide range of applications most importantly in military due to its stealth and precise location capability of threats. Two approaches are followed for emitter location estimation, either to use a single mobile detection system or to use multiple static platforms for signal reception. Direction/angle of arrival and various range estimation techniques allows target localization. Mapping interfaces are used to provide a visual interpretation to the mathematical results. In case of multiple platform systems the mapping module also provides triangulation capability. In this paper we have discussed various trends that are persisting in the form of features incorporated in the target mapping modules, different techniques to extract the information from the Passive emitter location system and to bring it on the visual panel. Various passive emitter systems have been considered and their target mapping modules are compared with respect to different benchmarks.

Strategies for information injection for networks estimating emitter location

This paper considers the problem of emitter location in the presence of an adversary able to inject false information, where both the viewpoints of the adversary and locating network are considered. We begin by developing adversary strategies, which focus on degrading and redirecting the locating network. The locating network uses the time difference of arrival (TDOA) method and estimates the emitter location using both nonlinear least squares (LS) and the robust least median squares (LMS). Specifically, we determine the false sensor position the adversary should inject that maximally impacts the locating network by 1) minimizing the network’s accuracy, and 2) redirecting the network’s emitter location estimate. Similarly, we formulate a network’s strategy for detecting the adversary’s injection and develop a detector able to determine its presence under both adversary strategies. We present both theoretical and numerical results illustrating the effectiveness of the developed strategies.

Gold-MUSIC: A Variation on MUSIC to Accurately Determine Peaks of the Spectrum

This paper presents a new way of accurately determining peaks of the MUSIC (“Multiple emitter location and signal parameter estimation,” R. O. Schmidt, IEEE Trans. Antennas and Propagation, vol. AP-34, no. 3, pp. 276-280, Mar. 1986) spectrum, here considered from the point of view of estimating the directions of arrival (DOAs) of narrowband signals. It can be used, with any smart antenna geometry and for any purpose where MUSIC is applicable. The MUSIC algorithm for DOA estimation evaluates the MUSIC spectrum for various angles and chooses the maxima or peaks as the angles of arrival. The values obtained depend on the interval at which the spectrum is evaluated. The coarser the interval, the less accurate are the results in case of MUSIC. To improve accuracy and not depend on the interval, Root-MUSIC (“Direction finding for diversely polarized signals using polynomial rooting,” A. J. Weiss and B. Friedlander, IEEE Trans. Signal Processing, vol. 41, no. 5, pp. 1893-1905, May 1993), which involves finding the roots of a polynomial, is available. However, Root-MUSIC is applicable, in its original form, only to uniform linear arrays (ULA). The gold-MUSIC algorithm proposed in this paper is a two-stage process. The first stage evaluates the objective function at coarse intervals and determines peaks followed by an iterative approach based on gold-section univariate (GSU) minimization (Algorithms for Minimization Without Derivatives, R. Brent, Englewood Cliffs, NJ, USA: Prentice-Hall, 1983) to find accurate values of the peaks. If the number of peaks found so far is equal to the number of estimated peaks, the algorithm stops with this first stage. The second stage is an iterative step for fine resolution using finer intervals around the peaks found so far for finding peaks that were missing in previous iterations. This paper, also presents a method, based on a partitioning algorithm for estimating the number of emitters. The performance of gold-MUSIC is described, including its advantages and comparison of time complexities for MUSIC, Root-MUSIC and gold-MUSIC. The proposed algorithm gives good results even when the number of snapshots is small. This gives it an additional computational advantage. It does not compromise on the resolving power of MUSIC.

Optimization of receiver arrangements for passive emitter localization methods

Passive localization of an object from its emission can be based on time difference of arrival or phase shift measurements for different receiver groups in sensor arrays. The accuracy of the localization primarily depends on accurate time and/or phase measurements. The frequency of the emission and the number and arrangement of the receivers mainly effect the resolution of the emitter localization. In this paper optimal receiver positions for passive localization methods are proposed, resulting in a maximal resolution for the emitter location estimate. The optimization is done by analyzing the uncertainty of the emitted signal, including its frequency. The technique has been developed specifically for ultrasound signals obtained from omnidirectional transducers, although the results apply for other application using passive localization techniques.

Krylov methods in time‐reversal imaging by multiple‐signal‐classification.

Multiple signal classification (MUSIC) has been used to form images and identify sound sources since 1986 [R. O. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Trans. Antennas Propag., AP‐34, 276–280 (1986)]. In active sonar imaging of point targets, the MUSIC method can be used to estimate the range of the time‐reversal operator. In this context, the method is related to the decomposition of the time‐reversal operator method. Typical implementations of these methods utilize measurements of the entire time‐reversal operator, and require computations of its eigenvalues and eigenvectors. By contrast, we show that Krylov iterative methods can be used to perform MUSIC imaging with relatively few acoustic excitations. Furthermore, by using the Lanczos technique, no eigenvalues or eigenvectors need be computed. Rather, an orthonormal basis for the range space of the time‐reversal operator can be constructed directly from the received data. Most of the necessary computing is performed by the array itself, performing as a kind of “analog computer.” Finally, we show that useful images can be formed from one iteration to the next, while the data are being collected.

Online Optimization of Receiver Trajectories for Scan-Based Emitter Localization

Scan-based emitter localization is a passive geolocation technique for stationary pulsed radars. In scan-based localization, knowledge of radar scan rate and radar beam intercept times are used to determine subtended angles of the radar location from receiver pairs. A collection of subtended angles is utilized to estimate the radar location. The paper presents a maximum likelihood (ML) scan-based localization algorithm and derives the Cramer-Rao lower bound (CRLH) for emitter location estimate. Based on maximization of the determinant of the Fisher information matrix, online gradient-based receiver trajectory optimization algorithms are developed. The effectiveness of the proposed algorithms is illustrated with simulation examples.

Associative memories for third-generation passive ranging

An exciting discovery has recently been made in the long history of passive ranging. The simple approach of associative memories has been found to be very effective. Numerical experiments show that, through training, a memory matrix can be determined that produces an accurate emitter location estimate based on few noisy observations and minimal computing. If these results hold up under more stringent tests and for more realistic applications, there will be a great impact on airborne passive ranging in the near future.