HF multipath passive single site radio location

This paper considers the problem of passive geolocation for the case of HF multipath propagation. A new technique is developed for the estimation of interpath time delay applying the multiple signal classification (MUSIC) superresolution spectral estimation method. The technique samples the signals received by two spatially separated antennas to compute the normalized MUSIC cepstrum. The method is applied to experimental data in a preliminary proof-of-concept analysis     

Geolocation of frequency-hopping transmitters via satellite

An analysis of satellite-communications terminal geolocation performed by means of interception of ground terminal uplink transmissions in which a number of spaceborne interceptors transpond the frequency band of interest to terrestrial location for processing is presented. Interception regions for prototypical terminals and satellites are calculated and the results are presented parametrically as a function of uplink signal-to-noise ratio (SNR). The optimum angular separation of the interceptor satellites is found, and the effect of nonoptimal separation is discussed, as are the practical limitations involved in implementing this geolocation system     

DGPS/IMU integration-based geolocation system: Airborne experimental test results

This paper addresses differential global positioning system (DGPS)/inertial measurement unit (IMU) integration-based geolocation system developed for airborne remote sensing cameras. First, we provide a brief review on sensor calibration, alignment and sensor fusion as background material of this research. After presenting those background material, as a main part of this paper we present a geolocation algorithm designed for an airborne imaging system. The geolocation system developed is tested through actual airborne experiments. For the verification of the geolocation system developed, we compare initial stationary states of the airplane before-taking off with states after-landing. From the actual test results, we find that it is critical to do an accurate time synchronization between IMU, DGPS, and airborne images, and to compensate for the data delay occurred during the network transfer.     

Passive localization of moving emitters using out-of-planemultipath

The purpose of this work is to establish how a moving emitter, such as a jammer, can be localized by a passive receiver through the use of out-of-plane multipath signals reflected by the terrain. This is a novel localization technique that assumes no a priori knowledge of the localization of the multipath sources. The emitter parameters of range, heading, velocity, and altitude are estimated by exploiting the correlation between the direct-path signal and the delayed and Doppler modulated signals. Two basis assumptions about the scattering properties of the terrain lead to different maximum likelihood estimators (MLEs). The Cramer-Rao lower bounds (CRLB) are used to study estimator performance versus emitter velocity for each case. The proposed estimators are successfully demonstrated using field data collected at White Sands Missile Range (WSMR) during the DARPA/Navy Mountaintop program     

Global node selection for localization in a distributed sensor network

This work considers the problem of selecting the best nodes for localizing (in the mean squared (MS) position error sense) a target in a distributed wireless sensor network. Each node consists of an array of sensors that are able to estimate the direction of arrival (DOA) to a target. Different computationally efficient node selection approaches that use global network knowledge are introduced. Performance bounds based on the node/target geometry are derived, and these bounds help to determine the necessary communication reach of the active nodes. The resulting geolocation performance and energy usage, based on communication distance, is evaluated for a decentralized extended Kalman filter (EKF) that is exploiting the different selection approaches.     

Geolocation of a known altitude object from TDOA and FDOA measurements

Most satellite systems for locating an object on Earth use only time difference of arrival (TDOA) measurements. When there are relative motions between an emitter and receivers, frequency difference of arrival (FDOA) measurements can be used as well. Often, the altitude of an object is known (it is zero, for example) or can be measured with an altimeter. Two sets of geolocation solutions are proposed which exploit the altitude constraint to improve the localization accuracy. One is for TDOAs alone and the other for the combination of TDOA and FDOA measurements. The additional complexity by imposing the constraint is a one-dimensional Newton's search and the rooting of a polynomial. The covariance matrices of the new estimators are derived under a small measurement noise assumption and shown to attain the constrained Cramer-Rao lower bound (CRLB). When there is a bias error in the assumed altitude, using the altitude constraint will introduce a bias to the solution. Since applying the constraint decreases the variance, there is a tradeoff between variance and bias in the mean square error (MSE). The maximum allowable altitude error such that the constraint solution will remain superior to the unconstraint is given. Simulation results are included to corroborate the theoretical development.     

ANALYSIS OF LOCATION ACCURACY FOR AN EMITTER USING SATELLITE- MOUNTED INTERFEROMETER

ＡＮＡＬＹＳＩＳＯＦＬＯＣＡＴＩＯＮＡＣＣＵＲＡＣＹＦＯＲＡＮＥＭＩＴＴＥＲＵＳＩＮＧＳＡＴＥＬＬＩＴＥ┐ＭＯＵＮＴＥＤＩＮＴＥＲＦＥＲＯＭＥＴＥＲＺｈｏｕＹｉｙｕ（周一宇）,ＧｕｏＺｈｉｇａｎｇ（郭志刚）（ＮａｔｉｏｎａｌＵｎｉｖｅｒｓｉｔｙｏｆＤ...     

PASSIVE LOCATION AND ACCURACY ANALYSIS USING TDOA INFORMATION OF MULTI-STATIONS

ＰＡＳＳＩＶＥＬＯＣＡＴＩＯＮＡＮＤＡＣＣＵＲＡＣＹＡＮＡＬＹＳＩＳＵＳＩＮＧＴＤＯＡＩＮＦＯＲＭＡＴＩＯＮＯＦＭＵＬＴＩ┐ＳＴＡＴＩＯＮＳＹａｎｇＬｉｎ（杨林）,ＺｈｏｕＹｉｙｕ（周一宇）,ＳｕｎＺｈｏｎｇｋａｎｇ（孙仲康）（Ｉｎｓｔｉｔｕｔｅｏｆ...     

Uncertainty ellipses and their application to interval estimation of emitter position

A method of interval estimation of position of an object emitting electromagnetic energy is presented. The problem is considered in cases of known and unknown errors of emitter position determination. Precise expressions concerning two-dimensional confidence regions for unknown position of the emitter have been obtained. Uncertainty regions defined as error ellipses and confidence ellipses have been determined. Qualitative and quantitative comparison of considered regions have been made. The presented approach and obtained results may be useful in electronic intelligence (ELINT) and electronic warfare (EW) applications, in radio navigation, ballistics, and in rescue operations at sea as well.     

Sensitivity analysis of dual-satellite geolocation

An analytic solution is presented for the linearized estimation problem arising from the dual-satellite geolocation of the source of a narrowband signal using time- and frequency-difference-of-arrival (TDOA and FDOA, respectively) observations and an altitude constraint. This solution is used to analyze the covariance matrix of the resultant source location estimate, along with the sensitivity of its mean to errors in the presumed source altitude and velocity, and the measured or predicted positions and velocities of the satellites. Following the practice of differential Global Positioning System, the technique of differential calibration is used to reduce or eliminate various sources of solution bias which would otherwise require tight, and consequently expensive, individual calibration     

Passive localization by a single moving observer using TOA only with unknown SRI: Observability analysis and algorithm

Passive localization by a single moving observer using Time of Arrival (TOA) only with an unknown Signal Repetition Interval (SRI) is investigated in this paper. Observability analysis is performed first. The observability condition for uniquely determining the emitter position and SRI is derived. The conditional Cramer-Rao Lower Bound (CRLB) is also analyzed. It is found that the ambiguity of the SRI integer of the first TOA does not affect the theoretical estimation precision of the emitter position and SRI. A Reference-Fixed Differential TOA (RFDTOA)-based Iterative Maximum Likelihood Estimator (IMLE) is proposed, which only needs O(M) computational operations. Theoretical analysis and simulation results show that the Mean Square Error (MSE) of the proposed algorithm could attain the CRLB with moderate Gaussian measurement noise.     

A Linear-correction Least-squares Approach for Geolocation Using FDOA Measurements Only

  A linear-correction least-squares(LCLS) estimation procedure is proposed for geolocation using frequency difference of arrival (FDOA) measurements only. We first analyze the measurements of FDOA, and further derive the Cram閞-Rao lower bound (CRLB) of geolocation using FDOA measurements. For the localization model is a nonlinear least squares(LS) estimator with a nonlinear constrained, a linearizing method is used to convert the model to a linear least squares estimator with a nonlinear constrained. The Gauss-Newton iteration method is developed to conquer the source localization problem. From the analysis of solving Lagrange multiplier, the algorithm is a generalization of linear-correction least squares estimation procedure under the condition of geolocation using FDOA measurements only. The algorithm is compared with common least squares estimation. Comparisons of their estimation accuracy and the CRLB are made, and the proposed method attains the CRLB. Simulation results are included to corroborate the theoretical development.     

Solution and performance analysis of geolocation by TDOA

One method of geolocation is based on measuring the time difference of arrivals (TDOAs) of a signal received by three or four geostationary satellites. The received signals are cross-correlated to determine the TDOAs and a set of nonlinear equations are solved to produce the location estimate. An exact solution for the transmitter position is derived for the three or four receiver cases. Extension of the solution method to more receivers is straightforward. An analysis of the performance of the system is given, together with expressions for predicting the localization mean-square errors (MSEs) and bias, and the Cramer-Rao bound. Both precision in TDOA measurements and the relative geometry between receivers and transmitter affect the localization accuracy. The geometric factors act as multipliers to the TDOA variance in the bias and MSE formulae. A study of the dependency of the geometric factors on transmitter position and satellite spacings are provided, as well as simulation results     

Passive localization of frequency-agile radars from angle andfrequency measurements

It is well known that the position of a stationary radar can be estimated by a single moving observer from angle and/or frequency measurements taken passively at different points in its trajectory. Depending on the measurement set different localization methods result: the bearing method (BM), the frequency method (FM), and the combined method (CM). Previous studies analyze the three methods on the basis of constant emitter frequencies. However, radars with constant emitter frequencies are not realistic. Frequency drift and frequency hopping have to be taken into account. Therefore, to include radars the emitter model has been extended by drift and frequency hopping in this study, and the estimation methods have been reanalyzed. The effects of the model extensions become transparent in a parametric Cramer-Rao (CR) analysis. The results obtained in this way are confirmed by Monte Carlo simulations taking maximum likelihood (ML) as estimation procedure     

Least squares range difference location

An array of n sensors at known locations receives the signal from an emitter whose location is desired. By measuring the time differences of arrival (TDOAs) between pairs of sensors, the range differences (RDs) are available and it becomes possible to compute the emitter location. Traditionally geometric solutions have been based on intersections of hyperbolic lines of position (LOPs). Each measured TDOA provides one hyperbolic LOP. In the absence of measurement noise, the RDs taken around any closed circuit of sensors add to zero. A bivector is introduced from exterior algebra such that when noise is present, the measured bivector of RDs is generally infeasible in that there does not correspond any actual emitter position exhibiting them. A circuital sum trivector is also introduced to represent the infeasibility; a null trivector implies a feasible RD bivector. A 2-step RD Emitter Location algorithm is proposed which exploits this implicit structure. Given the observed noisy RD bivector Δ, (1) calculate the nearest feasible RD bivector Δˆ, and (2) calculate the nearest point to the ( ₃ⁿ) planes of position, one for each of the triads of elements of Δˆ. Both algorithmic steps are least squares (LS) and finite. Numerical comparisons in simulation show a substantial improvement in location error variances     

A new method for finding electromagnetic emitter location

The position of a source of radiation is often obtained from bearing data, taken over an interval of time, and combining it with navigation data. A new method using total least squares (TLS) has been suggested for the accurate estimation of an emitter location when bearing observation errors are random. Further, an iterative two-stage approach involving TLS and Kalman filtering is developed for accurate estimation of the emitter location when bearing observation errors are an algebraic sum of random and systematic errors. The elegance and efficacy of the proposed methods are illustrated through digital computer simulated examples     

传感器位置误差条件下仅用到达频率差的无源定位性能分析

传感器自身的位置误差对辐射源的无源定位精度可能有较大影响,详细分析并推导了在存在传感器位置误差条件下,仅使用到达频率差(FDOA)参数对辐射源定位时,定位精度的克拉美罗下限(CRLB)和均方误差(MSE).在传感器位置误差条件下,提出仅用FDOA来同时估计辐射源和传感器位置的泰勒级数方法,并证明该定位方法理论上的MSE...     

基于短时时差序列的无源定位方法

针对脉冲辐射源定位问题,提出了一种基于短时时差(TDOA)序列的多站无源定位新方法.首先建立了TDoA序列模型,然后推导了该方法定位误差的克拉美罗下限(CRLB),并提出了一种高效的解算方法--两步定位法(TSLM):第1步利用TDOA序列线性估计出TDOA及其变化率信息,第2步基于TDOA及其变化率信息进行定位.典型...     

Target localization based on cross-view matching between UAV and satellite

Matching remote sensing images taken by an unmanned aerial vehicle (UAV) with satellite remote sensing images with geolocation information. Thus, the specific geographic location of the target object captured by the UAV is determined. Its main challenge is the considerable differences in the visual content of remote sensing images acquired by satellites and UAVs, such as dramatic changes in viewpoint, unknown orientations, etc. Much of the previous work has focused on image matching of homologous data. To overcome the difficulties caused by the difference between these two data modes and maintain robustness in visual positioning, a quality-aware template matching method based on scale-adaptive deep convolutional features is proposed by deeply mining their common features. The template size feature map and the reference image feature map are first obtained. The two feature maps obtained are used to measure the similarity. Finally, a heat map representing the probability of matching is generated to determine the best match in the reference image. The method is applied to the latest UAV-based geolocation dataset (University-1652 dataset) and the real-scene campus data we collected with UAVs. The experimental results demonstrate the effectiveness and superiority of the method.     

Emitter Location Independent of Systematic Errors in Direction Finders

A scheme is suggested for the passive location of radio emitter position by using a mobile direction finder. The vehicle carrying the direction finder is made to maneuver such that the apparent direction of arrival is held constant. The resulting trajectory of the vehicle is a logarithmic spiral. The true direction of arrival can be obtained by monitoring the parameters of the spiral trajectory without using the value of the direction fimder reading. Two specific algorithms to eliminate direction finder bias are presented and their sensitivity to random errors in measurement assessed.