LFM Radar Source Passive Localization Algorithm Based on Range Migration

Traditional single-satellite passive localization algorithms are influenced by frequency and angle measurement accuracies,resulting in error estimation of emitter position on the order of kilometers.Subsequently,a single-satellite localization algorithm based on passive synthetic aper-ture(PSA)was introduced,enabling high-precision positioning.However,its estimation of azimuth and range distance is considerably affected by the residual frequency offset(RFO)of uncoopera-tive system transceivers.Furthermore,it requires data containing a satellite flying over the radia-tion source for RFO search.After estimating the RFO,an accurate estimation of azimuth and range distance can be carried out,which is difficult to achieve in practical situations.An LFM radar source passive localization algorithm based on range migration is proposed to address the dif-ficulty in estimating frequency offset.The algorithm first provides a rough estimate of the pulse repetition time(PRT).It processes intercepted signals through range compression,range interpola-tion,and polynomial fitting to obtain range migration observations.Subsequently,it uses the changing information of range migration and an accurate PRT to formulate a system of nonlinear equations,obtaining the emitter position and a more accurate PRT through a two-step localization algorithm.Frequency offset only induces a fixed offset in range migration,which does not affect the changing information.This algorithm can also achieve high-precision localization in squint scenar-ios.Finally,the effectiveness of this algorithm is verified through simulations.

Passive Localization of Signal Source Based on UAVs in Complex Environment

For the influence caused by multipath fading and non-line-of-sight(NLOS)transmission,it is challenging to accurately localize a moving signal source in complex environment by using the wireless sensor network(WSN)on the ground.In this paper,we establish a special WSN in the sky to address this challenge,where each sensor is loaded on an unmanned aerial vehicle(UAV)and the operation center of all the UAVs is fixed on the ground.Based on the analyzing of the optimal distribution and the position error calibration of all the sensors,we formulate the localization scheme to estimate the position of the target source,which combines the time difference of arrival(TDOA)method and the frequency difference of arrival(FDOA)method.Then by employing the semidefinite programming approach,we accurately obtain the position and velocity of the signal source.In the simulation,the validity of the proposed method is verified through the performance comparison.

Novel passive localization algorithm based on weighted restricted total least square

A novel multi-observer passive localization algorithm based on the weighted restricted total least square （WRTLS） is proposed to solve the bearings-only localization problem in the presence of observer position errors. Firstly, the unknown matrix perturbation information is utilized to form the WRTLS problem. Then, the corresponding constrained optimization problem is transformed into an unconstrained one, which is a generalized Rayleigh quotient minimization problem. Thus, the solution can be got through the generalized eigenvalue decomposition and requires no initial state guess process. Simulation results indicate that the proposed algorithm can approach the Cramer-Rao lower bound （CRLB）, and the localization solution is asymptotically unbiased.

ALGORITHM FOR ACOUSTIC PASSIVE LOCALIZATION WITH DUAL ARRAYS

Aiming at the problem of 3D target localization by time delay estimation, this paper proposes a new acoustic passive localization method, which can provide high precision localization estimation. The first step of the two-stage algorithm is to measure the azimuth angle and pitch angle at each single array, which can obtain high precision angle estimation but low precision range estimation. And in the second step, the location of acoustic source is calculated from the angles measured above and geometry position of the two arrays. Then the accuracy of localization estimation is discussed in theory, and the influence factors and localization error are analyzed by simulation. The simulation results validate the performance of the proposed algorithm, and show the precision of localization estimation with dual arrays is superior to single array.

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.

Novel passive localization algorithm based on double side matrix-restricted total least squares

In order to solve the bearings-only passive localization problem in the presence of erroneous observer position, a novel algorithm based on double side matrix-restricted total least squares （DSMRTLS） is proposed. First, the aforementioned passive localization problem is transferred to the DSMRTLS problem by deriving a multiplicative structure for both the observation matrix and the observation vector. Second, the corresponding optimization problem of the DSMRTLS problem without constraint is derived, which can be approximated as the generalized Rayleigh quotient minimization problem. Then, the localization solution which is globally optimal and asymptotically unbiased can be got by generalized eigenvalue decomposition. Simulation results verify the rationality of the approximation and the good performance of the proposed algorithm compared with several typical algorithms.

Theory of passive localization for underwater sources based on acoustic ray modeling

The theory of passive localization for underwater sources based on acoustic ray channel modeling is discussed. The principles of channel modeling in Ray-theory, determination of eigenrays which connect source and receiver, analysis of DOA arriving structure and time delay spectrum arriving structure, their relationship to source location are given in the paper. Source location is estimated by matching measured DOA and TDS to their calculated counterparts. The method of Ray-theory based passive localization features its simplicity, less calculation, short array aperture and robust performance to environment parameters, as compared with those methods based on Normal Mode theory.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

A Residual Frequency Offset Estimation Method Based on Range Migration Fitting

Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.

Research on Acoustic Localization Algorithm Based on Dual Four-Element Arrays

The passive acoustic locating technology is widely used in military fields. The traditional locating method with single array has low precision of distance estimation, but comparatively high precision of angle estimation. According to the characteristic, the algorithm for acoustic passive localization based on the azimuth angle and geometry position of the two arrays is derived to estimate the target distance, and the simulation for the factors that affect the localization precision also proceeds. The result of the simulation shows the precision of localization estimation with dual arrays is superior to that of single array, and the passive localization algorithm based on dual array can meet the practical demands.

Influence of Synchronization Impairments on an Experimental TDOA/FDOA Localization System

In Electronic Warfare, and more specifically in the domain of passive localization, accurate time synchronization between platforms is decisive, especially on systems relying on TDOA （time difference of arrival） and FDOA （frequency difference of arrival）. This paper investigates this issue by presenting an analysis in terms of final localization performance of an experimental passive localization system based on off-the-shelf components. This system is detailed, as well as the methodology used to carry out the acquisition of real data. This experiment has been realized with two different kinds of clock. The results are analyzed by calculating the Allan deviation and time deviation. The choice of these metrics is explained and their properties are discussed in the scope of an airborne bi-platform passive localization context. Conclusions are drawn regarding the overall localization performance of the system.

Shallow water source localization using a mobile short horizontal array

This paper presents an approach to the challenging is- sue of passive source localization in shallow water using a mobile short horizontal linear array with length less than ten meters. The short array can be conveniently placed on autonomous underwa- ter vehicles and deployed for adaptive spatial sampling. However, the use of such small aperture passive sonar systems makes it difficult to acquire sufficient spatial gain for localizing long-range sources. To meet the requirement, a localization approach that employs matched-field based techniques that enable the short ho- rizontal linear array is used to passively localize acoustic sources in shallow water. Furthermore, the broadband processing and inter-position processing provide robustness against ocean en- vironmental mismatch and enhance the stability of the estimation process. The proposed approach＇s ability to localize acoustic sources in shallow water at different signal-to-noise ratios is examined through the synthetic test cases where the sources are located at the endfire and some other bearing of the mobile short horizontal linear array. The presented results demonstrate that the positional parameters of the estimated source build up over time as the array moves at a low speed along a straight line at a constant depth.

A Fast and Accurate LEO Satellite-Based Direct Position Determination Assisted by TDOA Measurements

This paper focuses on the trusted vessel position acquisition using passive localization based on the booming low-earth-orbit(LEO) satellites. As the high signal-to-noise ratio(SNR) reception cannot always be guaranteed at LEO satellites, the recently developed direct position determination(DPD)is adopted. For LEO satellite-based passive localization systems, an efficient DPD is challenging due to the excessive exhaustive search range leading from broad satellite coverage. In order to reduce the computational complexity, we propose a time difference of arrival-assisted DPD(TA-DPD) which minimizes the searching area by the time difference of arrival measurements and their variances. In this way, the size of the searching area is determined by both geometrical constraints and qualities of received signals, and signals with higher SNRs can be positioned more efficiently as their searching areas are generally smaller.Both two-dimensional and three-dimensional passive localization simulations using the proposed TA-DPD are provided to demonstrate its efficiency and validity. The superior accuracy performance of the proposed method, especially at low SNRs conditions, is also verified through the comparison to conventional two-step methods. Providing a larger margin in link budget for satellite-based vessel location acquisition,the TA-DPD can be a competitive candidate for trusted marine location service.

Novel method for radial velocity difference estimation of moving targets with wideband signals

For the frequency difference of arrival （FDOA） esti-mation in passive location, this paper transforms the frequency difference estimation into the radial velocity difference estimation, which is difficult to achieve a high accuracy due to the mismatch between the sampling period and the pulse repetition interval. The proposed algorithm firstly estimates the point-in-time that each pulse arrives at two receivers accurately. Secondly two time of arrival （TOA） sequences are subtracted. And final y the radial ve-locity difference of a target relative to two stations with the least square method is estimated. This algorithm only needs accurate estimation of the time delay between pulses and is not influenced by parameters such as frequency and modulation mode. It avoids transmitting a large amount of data between two stations in real time. Simulation results corroborate that the performance is bet-ter than the arithmetic average of the Cramer-Rao lower bound （CRLB） for monopulse under suitable conditions.

Passive source localization using importance sampling based on TOA and FOA measurements

Passive source localization via a maximum likelihood （ML） estimator can achieve a high accuracy but involves high calculation burdens, especially when based on time-of-arrival and frequency-of-arrival measurements for its internal nonlinearity and nonconvex nature. In this paper, we use the Pincus theorem and Monte Carlo importance sampling （MCIS） to achieve an approximate global solution to the ML problem in a computationally efficient manner. The main contribution is that we construct a probability density function （PDF） of Gaussian distribution, which is called an important function for efficient sampling, to approximate the ML estimation related to complicated distributions. The improved performance of the proposed method is at- tributed to the optimal selection of the important function and also the guaranteed convergence to a global maximum. This process greatly reduces the amount of calculation, but an initial solution estimation is required resulting from Taylor series expansion. However, the MCIS method is robust to this prior knowledge for point sampling and correction of importance weights. Simulation results show that the proposed method can achieve the Cram6r-Rao lower bound at a moderate Gaussian noise level and outper- forms the existing methods.

A novel bearing-assisted TDOA-GROA approach for passive source localization

Purpose–The passive source localization(PSL)problem using angles of arrival(AOA),time differences of arrival(TDOA)or gain ratios of arrival(GROA)is generally nonlinear and nontrival.In this research,the purpose of this paper is to design an accurate hybrid source localization approach to solve the PSL problem.The inspiration is drawn from the fact that the bearings,TDOAs and GROAs are complementary in terms of their geometry properties.Design/methodology/approach–The maximum-likelihood(ML)method is reexamined by using hybrid measurements.Being assisted by the bearings,a new hybrid weighted least-squares(WLS)method is then proposed by jointly utilizing the bearing,TDOA and GROA measurements.Findings–Theoretical performance analysis illustrates that the mean-square error of the ML or WLS method can attain the Cramér-Rao lower bound for Gaussian noiseover small error region.However,the WLS method has much lower computational complexity than the ML algorithm.Compared with the AOA-only,TDOA-only,AOA-TDOA,TDOA-GROA methods,the localization accuracy can be greatly improved by combining the AOAs,TDOAs and GROAs,especially for some specific geometries.Originality/value–A novel bearing-assisted TDOA-GROA method is proposed for source localization,and a new hybrid WLS estimator is presented inspired from the fact that the bearings,TDOAs and GROAs are complementary in terms of their geometry properties.