Sharif Digital Repository

The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. The objective of the present study is to propose a new adaptive beamformer which is robust against direction-of-arrival (DOA) mismatch and its convergence rate is not sensitive to the presence of the DS. This method is applicable to the arrays with specific structure such as the linear array. Our approach is based on the DS elimination from the training snapshots and the sub-array beamforming technique. To accomplish this goal, a blocking matrix which converts the primary data to the DS-free data is... 

Direction-of-arrival (DOA) estimation algorithms usually impose high computation burden and most of them are incapable of facing the coherent sources. In this paper, a new computationally efficient algorithm that is robust against the coherent sources is proposed. This method is based on a combination of the Maximum Likelihood (ML) and Orthogonal-Matching-Pursuit (OMP) algorithms. Simulation results show that the proposed algorithm has good performance in the small sample size cases and the coherency does not affect its performance  

For direction of arrival (DOA) estimation in compact arrays, a new approach based on time delay and amplitude estimation is presented for a known signal. The DOA can be accurately estimated without any calibration sources since the mutual coupling and multipath effects can be eliminated by the inherent mechanism of the proposed algorithm. The algorithm has significantly lower error and much less computational burden compared with the previous methods in high signal-to-noise ratio (SNR) conditions  

A comprehensive study is performed to investigate the performance of a non-uniform circular array interferometer in a real time 3-dimensional direction finder. The angular range of view is supposed to be 65 degrees vertically and 120 degrees horizontally, which is suitable for airborne applications. Interferometer is designed to work in the S, C and X bands. Regarding optimization process, the interferometer employs an eight element non-uniform circular array along with a phase reference antenna at the center of the array. Several quantities and parameters are studied, e.g., frequency behavior, origins of phase measurement errors, Signal to Noise Ratio (SNR) effect on phase measurement, and... 

This paper deals with the problem of estimating the position of emitters using only direction of arrival information. We propose an improvement of newly developed algorithm for position finding of a stationary emitter called sensitivity analysis. The proposed method uses Taylor series expansion iteratively to enhance the estimation of the emitter location and reduce position finding error. Simulation results show that our proposed method makes a great improvement on accuracy of position finding with respect to sensitivity analysis method  

This paper examines the problem of determining optimal sensors trajectories for localization of a moving radio source based on Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) measurements in situations in which sensors are constrained both in their movements and regions of operation. By considering the movement of the source and constrained movement of the sensors, a constraint problem is formed which is solved to determine optimal trajectories of the sensors for source tracking. The validity of the proposed algorithm is assessed by two different simulation scenarios and the results verify its proper operation with estimation error decreasing in consecutive steps... 

In CW forward scatter radars, Space-Time processing by 2-D FFT is used to estimate Doppler frequency shift and angle of arrival concurrently. 2-D periodogram and 2-D Capon methods are two famous spectral estimation methods which can be substituted for 2-D FFT. Here we will provide analysis of performance for these methods beside their cons and pros  

It was shown that the number of array elements must exceed the number of sources for subspace-based direction-of-arrival (DOA) estimation. But this is not practical for a direct-sequence code-division multiple access (DS-CDMA) wireless system, since the number of mobile users is very large. To remove the aforementioned restriction, a DOA estimator, employing the code-matched filters and parallel ESPRIT algorithms, is proposed. This algorithm does not use to search all angles such as MUSIC method. Besides, it is not necessary to use AIC and MDL criterion to estimate the number of sources in the proposed algorithm. Simulation results illustrates the appropriate performance of the new method  

This paper presents a new approach to sensor placement strategy in emitter localization problem which is based on Time Difference of Arrival (TDOA) measurements. The advantage of this method is its flexibility and capability of positioning sensors in constrained or non-stationary situations in which the positions of the sensors are restricted to certain portions of the space and/or needed to be changed repeatedly. The validity of the proposed algorithm is assessed by three different simulation scenarios and the results verify its proper operation  

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  

This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, which leads to a bias error. To compensate this bias error, a dictionary learning technique is suggested, which is based on minimizing a suitable cost function. We also propose an algorithm for the estimation of DOA from the sign of the measurements. It extends the iterative method with adaptive thresholding algorithm to the 1-b compressed sensing framework. Simulation results show the effectiveness... 

In triangulation (or angle of arrival) target localisation method, the surface of the Earth is approximated by a flat plate. This approximation, while acceptable for low-altitude observers (such as unmanned aerial vehicles), is not a correct model for high-altitude observers (such as low Earth orbit - LEO satellites). In this study, the authors have discussed triangulation method using a LEO satellite observer over a spherical surface and have shown that, using spherical trigonometry and singular value decomposition (SVD), a straight forward solution can be found for target localisation problem. Also, error bound is discussed and analysed using both SVD as well as simulation. © The... 

The Cramer-Rao lower bound for source localization based on Time Difference of Arrival and Frequency Difference of Arrival is investigated in this paper. The result is used for theoretical analysis of optimality in sensor placement. An optimal sensor-target geometry including sensors locations and velocities is presented and its properties is studied