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In this paper, a sparsity-aware target localization method in multiple-input-multiple-output (MIMO) radars by utilizing time difference of arrival (TDOA) measurements is proposed. This method provides a maximum likelihood (ML) estimator for target position by employing compressive sensing techniques. Also, for fast convergence and mitigating the mismatch problem due to grid discretization, we address a block-based search coupled with an adaptive dictionary learning technique. The Cramer-Rao lower bound for this model is derived as a benchmark. Simulations results are included to verify the localization performance  

in this paper detection and the accuracy of measurement of range, velocity and DOA in PCL radar for optimized parameters is considered. It is shown that, in order to measure the bistatic characteristics of a target, we can process the monostatic ambiguity function and extract the bistatic factors by proposed Algorithm. ©2006 IEEE  

In some well-known passive localization methods, when the number of equations equals the number of unknown object coordinates, there arise finite number of possible solutions. A localization disambiguation technique is required to identify the correct solution in these cases. As an example, the exact solution of time-difference-of-arrival (TDOA) based equations for four receiver sites, leads to a couple of solutions with only one of them being the true target position. This ambiguity, conventionally is resolved by using angle-of-arrival (AOA) measurements or using an additional receiver site which increase the cost and complexity of the system. In this paper a localization disambiguation... 

In some well-known passive localization methods, when the number of equations equals the number of unknown object coordinates, there arise finite number of possible solutions. A localization disambiguation technique is required to identify the correct solution in these cases. As an example, the exact solution of time-difference-of-arrival (TDOA) based equations for four receiver sites, leads to a couple of solutions with only one of them being the true target position. This ambiguity conventionally is resolved by using angle-of-arrival measurements or using an additional receiver site, which increase the cost and complexity of the system. In this paper, a localization disambiguation... 

In this article, localization of a maritime target using a passive multistatic radar system, consisting of a single receiver and a number of satellites as its transmitters, is investigated. The set of communication satellites and also the global navigation satellite system (GNSS), including GPS, Glonass, and Galileo, are employed as illuminators of opportunity. In the receiver, the reflected signals from the target along with the direct signal from the satellites are employed to extract a set of bistatic range measurements. Leveraging these measurements and the satellite's position information, a novel localization method considering zero height of maritime target and appropriate combination... 

Between 2010 and 2017, we have collected new optical and radar observations of the potentially hazardous asteroid (2102) Tantalus from the ESO NTT and Danish telescopes at the La Silla Observatory, and from the Arecibo planetary radar. The object appears to be nearly spherical, showing a low-amplitude light-curve variation and limited large-scale features in the radar images. The spin-state is difficult to constrain with the available data; including a certain light-curve subset significantly changes the spin-state estimates, and the uncertainties on period determination are significant. Constraining any change in rotation rate was not possible, despite decades of observations. The convex... 

Several target position finding methods are proposed in various papers mainly regarding sensor networks. However, the problem of position finding in passive radar systems is somewhat different from the general case of sensor networks. Generally, in a passive radar system, there are few receivers located at short distances when compared with the it distance from the target. In this case, a problem known as geometric dilution of precision (GDP) occurs, which considerably increases the error of many proposed methods. This phenomenon can even make the position finding equations non-solvable. Regarding this fact, we have developed a least mean square error (LMSE) based method, which uses both the... 

In this paper, the problem of locating a target in a distributed multiple-input multiple-output radar system using bistatic range measurements is addressed. An algebraic closed-form two-stage weighted least squares solution for the considered problem is developed and analyzed. In the first stage, we establish a set of linear equations by eliminating the nuisance parameters first and then we apply a weighted least squares estimator to determine the target position estimate. In the second stage, in order to improve the localization performance and refine the solution of the first stage, an estimate of the target position estimation error is obtained. The final solution is obtained by... 

In this paper, a fundamental investigation on the performance of localization problem in a distributed multiple-input multiple-output radar system using bistatic range (BR) and angle of arrival (AOA) measurements is conducted. The study is based on the Cramer-Rao lower bound (CRLB) for the target position under Gaussian measurement noise. We attempt to approximately compute the CRLB separately in the cases of BR-only and joint BRlAOA localization schemes and determine which factors can affect the CRLB values. The three factors the transmitter/receiver placement, the number of transmitters and receivers, and noise power levels are shown to be effective on the localization performance.... 

This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering the relationship between the nuisance parameter and the target position, a constrained weighted least squares (CWLS) problem is formulated, which is an indefinite quadratically constrained quadratic programming problem. Since the constraint is non-convex, it is a nontrivial task to find the global solution. For this purpose, an improved Newton's method is applied to the CWLS problem to estimate the target position. Numerical simulations are included to examine the algorithm's... 

This paper deals with the moving target localization problem from time delay and Doppler shift measurements in a distributed multiple-input multiple-output radar system. An algebraic closed-form two-stage weighted least squares solution is presented to locate the target position and velocity. In the first stage, a set of pseudo-linear equations is established by introducing and decreasing the nuisance parameters. Then, two quadratic equations are obtained in terms of the nuisance parameters by considering relationships among them and the target position and velocity. By applying the elimination method that gives the nuisance parameters and substituting them into the localization problem, the... 

This letter deals with the problem of moving target localization in distributed multiple-input multiple-output (MIMO) radar systems using time delay (TD) and Doppler shift (DS) measurements. The proposed solution to this problem consists of two stages. In the first stage, an initial estimation of target location is obtained by solving the formulated maximum likelihood (ML) problem based on the TD measurements. In the second stage, by recognizing the obtained position estimate in the previous stage as a priori data and exploiting the DS measurements, another ML problem is formulated, which is efficiently solved via a tractable numerical method to produce a simultaneous estimation of target... 

In this letter, an efficient estimator for 3-D target localization in distributed multiple-input multiple-output (MIMO) radars using time delay (TD) and angle of arrival (AOA) measurements is proposed. First, an approximately equivalent maximum likelihood (ML) estimation problem is formulated. Then, the aforementioned ML problem is recast into a convex optimization problem for which we derive a semi closed-form solution that eventually boils down to finding the roots of certain polynomials. Using numerical simulations, we demonstrate that the proposed estimator reaches the Cramer-Rao lower bound (CRLB) up to relatively high Gaussian measurement noise levels. Furthermore, the proposed method... 

In this study, a detector/estimator is proposed for compressed sensing radars, which does not need to reconstruct the radar signal, and which works directly from compressive measurements. More precisely, through direct processing of the measurements, and without the need for reconstructing the original radar signal, the system performs target detection, and then estimates range, Doppler frequency shift and radar cross section in the presence of a Gaussian clutter. It can be seen that for large compression ratios, the detection performance and estimation quality is comparable with a common radar system while having a much lower data rate and with less computational load  

In noise radars, measuring the cross-correlation between transmitted and received signals is a common method of signal processing. However, it brings a lot of unwelcome sidelobes that can mask weak echoes of far targets. There are many classical and modern methods of masking effect removal which are based on signal processing in the receiver side. In this study, a method of waveform design is presented and its ability to reduce masking effect is compared with that of radars using purely random waveforms. The method starts with choosing an arbitrary subsequence and continues with attaching new subsequences to the previous ones in a way that the sidelobe levels reduce. In addition, the... 

In noise radars, measuring the cross-correlation between transmitted and received signals is known as a common method of signal processing. However, it brings a lot of unwelcome sidelobes which can lean to masking weak echoes of far targets. There are many classical and modern methods of masking effect removal which are based on signal processing in the receiver side. A method of waveform design for decreasing this effect is presented and its efficiency is compared to purely random waveform generation method and CLEAN algorithm. Moreover, performance of collaborative using of receiver-based and transmitter-based techniques is considered  

There are inherent errors in target location and velocity measurement caused by bistatic geometry in addition to the errors that are caused in monostotic radars. In this paper, the accuracy of measurement with respect to some parameters like baseline variance and DOA estimation is considered and bistatic parameters sensitivity with respect together is formulated  

We consider the problem of corrupted radar super-resolution, a generalization of compressed radar super-resolution in which one aims to recover the continuous-valued delay-Doppler pairs of moving objects from a collection of corrupted and noisy measurements. The received signal in this type consists of contributions from objects, outlier and noise. While this problem is ill-posed in general, tractable recovery is possible when both the number of objects and corrupted measurements are limited. In this brief, we propose an atomic norm optimization in order to find the delay-Doppler pairs and the outlier signal. The objective function of our optimization problem encourages both sparsity in the... 

In a coherent pulse Doppler radar, ambiguity can occur in both range and radial velocity measurements. PRF staggering has been considered as one of the most effective ways by which these consequential blind speeds can be eliminated. As it stands the optimization of such staggering has not been convincingly provided in a clear format in past studies. In this article previously reported techniques have been studied and also a comprehensive simulation tool which provides interesting results based on different techniques is developed. Furthermore a comparison of various common staggering methods has been given and a cost function has been proposed to describe a figure of merit for each of the... 

This letter investigates the problem of threedimensional (3-D) target localization in multiple-input multipleoutput (MIMO) radars with distributed antennas, using hybrid timedelay (TD) and angle of arrival (AOA) measurements. We propose a closed-form positioning method based on weighted least squares (WLS) estimation. The proposed estimator is shown theoretically to achieve the Cramer-Rao lower bound (CRLB) under mild noise conditions. Numerical simulations also verify the theoretical developments. IEEE