Sharif Digital Repository

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... 

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  

This study presents and analyses a novel joint detection and parameters estimation of multiple targets using a co-located multiple input/multiple output radar with moving platform, in the presence of clutter and background noise. A notable feature of the proposed approach is that clutter cancellation is independent of received data. Moreover, to decrease the computational load, the authors propose to perform the target detection and parameters estimation by directly processing on the compressive measurements as opposed to Nyquist samples. © The Institution of Engineering and Technology  

Elliptic localization is an active range-based positioning technique that employs multiple transmitter-receiver pairs, each of which is able to provide separate bistatic range (BR) measurement. In this letter, an algebraic closed-form method for locating a single target from BR measurements using a distributed multiple-input multiple-output (MIMO) radar system is proposed. First, a set of linear equations is established by eliminating the nuisance parameters, and then, a weighted least squares estimator is employed to obtain the target position estimate. To refine the localization performance, the error in the initial solution is estimated in the sequence. The proposed method is shown... 

In this letter, the problem of target localization from bistatic range (BR) measurements in distributed multiple-input multiple-output radar systems is investigated. By introducing nuisance parameters, a pseudolinear set of BR equations is established. Then, a closed-form localization algorithm is developed, based on this pseudolinear set of equations and multistage weighted least squares estimation. This solution is shown analytically to attain the Cramer-Rao lower bound under the small Gaussian noise assumption. Simulations are included to support the theoretical studies. Unlike the existing studies where the variance of BR measurements is assumed to be independent of the corresponding... 

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.... 

Elliptic localization is a range-based positioning technique exploiting multiple transmitter-receiver pairs, each of which provides separate bistatic range (BR) measurements. In this paper, a novel computationally efficient solution for locating a single target from BR measurements in distributed MIMO radar systems is proposed. Due to nonconvex nature of the associated maximum likelihood (ML) estimation problem, its globally optimal solution is difficult to obtain. We first reformulate the ML estimation as a nonconvex constrained weighted least squares problem. Owing to special structure of the resulting problem, it is recast as a convex problem, whose exact solution can be obtained in... 

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 paper, an algebraic solution for elliptic localization in multiple-input multiple-output (MIMO) radar systems is proposed by taking the uncertainties in antenna positions and their clock parameters into account. Through nonlinear transformation and multi-stage processing, the target position is estimated in closed-form by successively utilizing the weighted least squares estimator. Theoretical analysis demonstrates that the proposed method is able to attain the Cramer-Rao lower bound (CRLB) performance under mild Gaussian error. The conditions for achieving the CRLB are derived as well. The numerical simulations confirm the analytical results and demonstrate significant 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... 

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... 

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... 

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... 

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 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... 

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... 

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  

Multiple-input multiple-output (MIMO) radars offer higher resolution, better target detection, and more accurate target parameter estimation. Due to the sparsity of the targets in space-velocity domain, we can exploit Compressive Sensing (CS) to improve the performance of MIMO radars when the sampling rate is much less than the Nyquist rate. In distributed MIMO radars, block CS methods can be used instead of classical CS ones for more performance improvement, because the received signal in this group of MIMO radars is a block sparse signal in a basis. In this paper, two new methods are proposed to improve the performance of the block CS-based distributed MIMO radars. The first one is a new... 

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...