In non-coherent Direction Of Arrival (DOA) estimation, the goal is to determine DOA based only on the magnitude of the received sensor array signal. The advantage of the non-coherent DOA estimation is its robustness against phase errors; despite phase errors present in both sensors and phase shifters, direction of arrival can be estimated. In this paper, DOA is estimated using a frequency estimation technique which can be simply implemented by discrete Fast Fourier Transform (FFT) methods. In addition, for removing the ambiguity and solving the nonlinear equations, a reference target with high power emission is used. Simulation results, in both linear and plane array cases show the efficiency and robustness of the proposed algorithm against phase errors.

This paper proceeds directions of arrival (DOA) estimation by a linear array. These years, some algorithms, e. g. Khatri-Rao approach, Nested array, Dynamic array have been proposed for estimating more DOAs than sensors. These algorithms can merely estimate uncorrelated sources. For Khatri-Rao approach, this is due to the fact that Khatri-Rao product discard the non-diagonal entries of the correlation matrix in opposed to Kronecker product. In this article, an algorithm named as Direction of Arrival (DOA) Estimation using Kronecker Subspace is proposed to solve more correlated sources than sensors via some properties of vectorization operator and Kronecker product. The simulations in different scenarios are presented considering various numbers of frames and correlation values, here. These verify our mathematical analysis. Furthermore, Cramer-Rao bound (CRB) which is a crucial criterion to estimate, is under investigating for DOA problem. Although, CRB for DOA estimation has been proposed before, it is applicable only for fewer sources than sensors. In this paper, CRB for more sources than sensor is derived by extending the dimensions with using both real and imaginary parts of the parameters. This bound is compared to the error of the presented algorithm. The simulations show that the error of the presented algorithm is merely 7 dB far from the CRB.

One of the ways to deal with the effect of jammers, especially intra-band jammers, is to use beamforming in multi-antenna systems. In this method, based on the direction of arrival (DOA) of the desired signal and DOA of the interferer, it is tried to design a beam pattern which has a peak in the direction of the desired source and a null in the direction of interferer. Depth of the null and its location depend on the information obtained about the angle of interferer from electronic support measure (ESM) system. In practice, it is not possible to obtain accurate information from the electronic support measure (ESM) system. In this paper, a beamforming method named estimation error probability based beamformer (EEPBF)which is robust to DOA estimation error has been proposed. Data dependent methods may be more efficient than the proposed method with the cost of more complexity of receiver structure required to extract information from the desired and interference signals, whilst for confronting the interferer our proposed method uses existing systems’ information, taking into account their errors. The proposed method keeps signal to interference plus noise ratio (SINR) in the order of signal to noise ratio (SNR) which can be obtained by error free DOA estimation methods. Simulation results show that the proposed method is more efficient than previous methods and traditional approaches.

In the most of DOA estimation methods, environmental noise model is considered to be uniform spatial white noise. However, in many applications this kind of modeling may not be appropriate and leads to considerable direction finding errors. Non-equal output noise power of array elements that causes nonuniform noise is one of these cases. The most important goal of this paper is the investigation and comparison of DOA estimation in presence of nonuniform noise using simulation as well as presenting a novel and effective method for DOA estimation in the mentioned situation. A novel low complexity algorithm for DOA estimation in presence of nonuniform spatial white noise is proposed. Additionally, the performance of the proposed method is simulated and compared with that of matrix completion based method and also iterative subspace estimation schemes for various parameters. The simulation results demonstrate that the proposed scheme achieves a considerable advantage over the existing schemes with remarkably lower complexity.

A new four elements compact antenna array is presented and discussed to achieve enhanced phase resolution without sacrificing the array output power. This structure inspired by the Ormia Ochracea’ s coupled ears. The analogy between this insect acute directional hearing capabilities and the electrically compact antenna array is used to enhance the array sensitivity to direction of arrival estimation of an electromagnetic wave. This four elements biomimetic compact array is composed of four strongly coupled antenna elements and two external coupling networks which are designed to enhance the phase resolutions between all antenna element outputs without decrease in the array output power. In other words, this four elements compact array extracts the same power level from the incident EM wave compared with regular array, while the output phase sensitivity is significantly enhanced. The simulation results confirm the advantages of this new compact array compared with the previously reported ones in the literature.

An Artificial Intelligence (AI) technique plays the most crucial factor to consider in energy utilization in a wireless sensor network (WSN). AI transforms industrial operations by optimizing the energy consumption in sensor nodes. As a result, it is crucial for improving sensor node location accuracy, particularly in unbalanced or Adhoc environments. Because of this, the purpose of this research is to improve the accuracy of the localization process in locations where sensor nodes encounter barriers or obstacles on a regular basis. The Bees Swarm Optimization (BSO) algorithm is used to segment sensor nodes in order to increase the accuracy of the Direction of Arrival (DoA) estimate between the anchor and unknown node pairs. Even in the presence of unbalanced conditions, the proposed DoA-BSO involving three separate bee colonies can identify plausible anchor nodes as well as segment nodes arranged in clusters. In order to obtain the intended result, the objective function is designed to take into consideration the hops, energy, and transmission distance of the anchor and unknown node pairs, among other factors. The studies are carried out in a large-scale WSN using sensor node pairs in order to determine the precision with which the DoA-BSO can be located. When comparing DoA-BSO to conventional approaches, the findings of the meta-heuristic algorithm show that it improves the accuracy and segmentation of nodes significantly

In this paper, an iterative algorithm for direction of arrival (DoA) estimation of coherent sources with a uniform circular array (UCA) is proposed. There is an additional error in the DoA estimationof signals after mapping UCA to virtual uniform linear array (VULA), due to approximation of beamspace transformation. This error depends on the direction of emitters. In the proposed algorithm, the dominant term of error is reduced using two beamformers. Then, the DoA of coherent sources are estimated by construction of Toeplitz covariance matrix and using the MUSIC algorithm. The processes of DoA estimation and reduction of the approximation error are doneiteratively. Also, an analytical expression is derived for the approximation of bias for DoA estimation of coherent sources. Simulation results show that the proposed algorithm has a better performance in comparison to the conventional methods.

In this paper, a new scheme named "modified coherent DiLL" is proposed for tracking direction of arrival of signals in direct-sequence code-division multiple-access systems. This scheme has a similar concept to the delay lock loop that is used for time synchronizing in CDMA systems. The proposed scheme is able to track the DOA of the arriving signals iteratively. The properties of the proposed scheme such as computational and mean square error are compared to the coherent and noncoherent DiLL. The new scheme consists of 2NK+O(K) computations, where Nand K are the number of antenna sensors and signal sources, respectively. The computation is two-folds and approximately the same Mean Square error as coherent DiLL scheme, while it does not require estimating. Data and phase of the received carrier signal. In addition, the computation of this method is approximately equal, and mean square error is half of the noncoherent DiLL.

Wideband linear frequency modulation (LFM) signals are widely used in systems such as radar, sonar and mobile. DOA estimation algorithms LFM signals rely on a large number of time frames (Snapshot). Therefore, they are not suitable for low power and real-time applications. In this paper, we present a low computation based estimation method based on the SPICE algorithm for linear arrays using the Fourier transform FFT. The method is to first develop the dechirping algorithm for LFM signals using the FFT converter, then modify the SPICE algorithm for uniform linear arrays (ULA), then obtain the DOA calculations for a few number of snapshots with low computational volumes. The simulation results of the proposed MSPICE algorithm (i. e. modified SPICE algorithm) show that the proposed algorithm is better than other algorithms such as MUSIC and SPICE. We have shown that the proposed method has acceptable accuracy in both low SNRs and low error in high SNRs. In addition, in terms of computational volume, it is much less than the MUSIC and SPICE methods and will have a good robustness compared to other methods.