Wideband DOA Estimation Method Based on Khatri-Rao Subspace with Uniform Focusing

2014 ◽  
Vol 687-691 ◽  
pp. 4064-4067
Author(s):  
Jin Zhang ◽  
Shi You Qi ◽  
Ai Xia Yong
Keyword(s):  
Theoretical Analysis ◽  
Estimation Method ◽  
Doa Estimation ◽  
Computation Complexity ◽  
Simulation Results ◽  
Effectiveness And Efficiency

A new wideband DOA estimation method based on Khatri-Rao subspace using uniform focusing is presented in this paper. Due to using the uniform focusing matrix which does not require pre-estimating the DOAs of signals in advance, its resolution is improved obviously and its computation complexity is reduced greatly. Meanwhile, it can also resolve more signals than the number of array sensors. Theoretical analysis and simulation results demonstrate the effectiveness and efficiency of the method.

scholarly journals DOA Estimation for Mixed Uncorrelated and Coherent Sources in Multipath Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Heping Shi ◽  
Wen Leng ◽  
Anguo Wang ◽  
Tongfeng Guo
Keyword(s):  
Linear Array ◽  
Estimation Method ◽  
Doa Estimation ◽  
Spatial Smoothing ◽  
Uniform Linear Array ◽  
Performance Simulation ◽  
Coherent Sources ◽  
Multipath Environment ◽  
Simulation Results ◽  
Effectiveness And Efficiency

A novel direction-of-arrival (DOA) estimation method is proposed to cope with the scenario where a number of uncorrelated and coherent narrowband sources simultaneously impinge on the far-field of a uniform linear array (ULA). In the proposed method, the DOAs of uncorrelated sources are firstly estimated by utilizing the property of the moduli of eigenvalues of the DOA matrix. Afterwards, the contributions of uncorrelated sources and the interference of noise are eliminated completely by exploiting the improved spatial differencing technique and only the coherent components remain in the spatial differencing matrix. Finally, the remaining coherent sources can be resolved by performing the improved spatial smoothing scheme on the spatial differencing matrix. The presented method can resolve more number of sources than that of the array elements and distinguish the uncorrelated and coherent sources that come from the same direction as well as improving the estimation performance. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

scholarly journals Sparse Cumulants Fitting for Direction-of-Arrival Estimation without Redundancy

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shuang Li ◽  
Xiaoxiao Jiang ◽  
Sai Ma ◽  
Yingguan Wang
Keyword(s):  
Gaussian Noise ◽  
Software Package ◽  
A Priori ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Array Output

A novel direction-of-arrival (DOA) estimation method is proposed based on the sparse cumulants fitting without redundancy. Firstly, we derive that some fourth order cumulants of the array output are redundant and therefore are removed to reduce computational complexity. Then, the left cumulants are sparsely represented on an overcomplete basis and the DOAs are resolved by using a software package. Despite introducing a high variance, the proposed method shows several advantages including the ability to detect more sources than sensors, high resolution, and robustness to all kinds of Gaussian noise. Besides, our method does not have to know, a priori, the number of sources. Simulation results are presented to illustrate the effectiveness and efficiency of the proposed method.

Studies on Novel Satellite Navigation and Positioning System Anti-Jamming Architecture

2014 ◽  
Vol 551 ◽  
pp. 417-424
Author(s):  
Wen Zhun Huang
Keyword(s):  
Theoretical Analysis ◽  
Frequency Domain ◽  
Power Analysis ◽  
Doa Estimation ◽  
Satellite Navigation ◽  
Architecture Design ◽  
Positioning System ◽  
Time Frequency ◽  
Simulation Results

During the course of studying how to improve and optimize the anti-jamming ability of the satellite navigation and positioning system, the satellite channel was faced with many types of jamming signals. It is difficult to adopt one kind of jamming suppression technology to effectively suppress all kinds of jamming. In order to solve these problems, a new anti-jamming architecture for satellite navigation and positioning system is proposed. That is adopting the jamming cognitive method combined with the time-frequency domain jamming type recognition, power analysis and jamming DOA estimation. Also, the anti-jamming architecture design of the satellite navigation and positioning system is given based on the jamming cognition. Theoretical analysis and simulation results show that the anti-jamming architecture can detect the different jamming signals according to different jamming types, simplify the jamming suppression algorithm, grade and classify to suppress jamming signals.

An Improved Direction-of-Arrival Estimation Method Based on Sparse Reconstruction

2012 ◽  
Vol 263-266 ◽  
pp. 135-138
Author(s):  
Xue Bing Han ◽  
Zhao Jun Jiang
Keyword(s):  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Sparse Reconstruction ◽  
Direction Of Arrival Estimation ◽  
Sensing Matrix ◽  
Signal Model ◽  
Multiple Measurement Vectors ◽  
Underdetermined System ◽  
Simulation Results

In this paper, we account for efficient approach of direction-of-arrival estimation based on sparse reconstruction of sensor measurements with an overcomplete basis. MSD-FOCUSS ( MMV Synchronous Descending FOCal Underdetermined System Solver) algorithm is developed against to sparse reconstruction in multiple-measurement-vectors (MMV) system where noise perturbations exist in both the measurements and sensing matrix. The paper shows how sparse-signal model of DOA estimation is established and MSD-FOCUSS is derived, then the simulation results illustrate the advantage of MSD-FOCUSS when it is used to solve the problem of DOA estimation.

scholarly journals Two-Dimensional DOA Estimation in Compressed Sensing with Compressive-Reduced Dimension-lp-MUSIC

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Weijian Si ◽  
Xinggen Qu ◽  
Lutao Liu ◽  
Zhiyu Qu
Keyword(s):  
Compressed Sensing ◽  
Estimation Method ◽  
Doa Estimation ◽  
Superior Performance ◽  
Two Dimensional ◽  
Improve Performance ◽  
Performance Simulation ◽  
Pair Matching ◽  
Reduced Dimension ◽  
Simulation Results

This paper presents a novel two-dimensional (2D) direction of arrival (DOA) estimation method in compressed sensing (CS) to remove the estimation failure problem and achieve superior performance. The proposed method separates the steering vector into two parts to construct two corresponding noise subspaces by introducing electric angles. Then, electric angles are estimated based on the constructed noise subspaces. In order to estimate the azimuth and elevation angles in terms of estimates of electric angles, arc-tangent operations are exploited. The arc-tangent is a one-to-one function and allows the value of the argument to be larger than unity so that the proposed method never fails. The proposed method can avoid pair matching to reduce the computational complexity and extend the number of snapshots to improve performance. Simulation results show that the proposed method can avoid estimation failure occurrence and has superior performance as compared to existing methods.

scholarly journals Grid Reconfiguration Method for Off-Grid DOA Estimation

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1209 ◽  
Author(s):  
Yun Ling ◽  
Huotao Gao ◽  
Guobao Ru ◽  
Haitao Chen ◽  
Boya Li ◽  
...  
Keyword(s):  
Bayesian Learning ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Sparse Bayesian Learning ◽  
Dynamic Parameters ◽  
Fission Process ◽  
Simulation Results ◽  
Grid Points ◽  
Grid Algorithms

Off-grid algorithms for direction of arrival (DOA) estimation have become attractive because of their advantages in resolution and efficiency over conventional ones. In this paper, we propose a grid reconfiguration direction of arrival (GRDOA) estimation method based on sparse Bayesian learning. Unlike other off-grid methods, the grid points of GRDOA are treated as dynamic parameters. The number and position of the grid points are varied iteratively via a root method and a fission process. Then, the grid gets reconfigured through some criteria. By iteratively updating the reconfigured grid, DOAs are estimated completely. Since GRDOA has fewer grid points, it has better computational efficiency than the previous methods. Moreover, GRDOA can achieve better resolution and relatively higher accuracy. Numerical simulation results validate the effectiveness of GRDOA.

scholarly journals DOA Estimation Method for CHAOS Radar System

2019 ◽  
Vol 17 (12.2) ◽  
pp. 35
Author(s):  
Hán Trọng Thanh ◽  
Nguyen Thanh Chuyen ◽  
Nguyen Xuan Quyen
Keyword(s):  
Antenna Array ◽  
Estimation Method ◽  
Matrix Pencil ◽  
Doa Estimation ◽  
Sampling Frequency ◽  
Radar System ◽  
Linear Antenna ◽  
Coherent Signals ◽  
Security Systems ◽  
Simulation Results

CHAOS signal has been drawing a lot of research interest recently due to its performance in security systems. In this paper, an approach to estimate the direction of target for Distributed Chaos Radar System using Total Forward - Backward Matrix Pencil (TFBMP) algorithm. This algorithm works directly on signal samples of signals received by M – element Uniform Linear Antenna array. Therefore, the correlation between the received signals does not significantly impact on its performance and efficiency. This fact permits us to estimate not only wideband incoherent signals but also wideband coherent signals. Furthermore, this algorithm can also extract the Direction Of Arrival (DOA) with only one snapshot of signal, which means that the sampling frequency in real time receivers can be considerably reduced. The simulation results for DOA of incoming CHAOS signals using the proposed approach will be shown and analyzed to verify its performance.

scholarly journals On the Analysis Performance of Updating Weight for Estimation Target of Drone System

2018 ◽  
Vol 208 ◽  
pp. 03009
Author(s):  
Kwan Hyeong Lee ◽  
Jae Hoon Lee
Keyword(s):  
Estimation Method ◽  
Direction Of Arrival ◽  
Simple Calculation ◽  
Low Power Consumption ◽  
Direction Of Arrival Estimation ◽  
Good Resolution ◽  
Paper Study ◽  
Computation Complexity ◽  
Music Algorithm ◽  
Simulation Results

In this paper, we propose the method which desired signal is estimated by updating the weight of the MVDR algorithm. The MUSIC algorithm is generally a lot of used in the direction of arrival estimation method. The MUSIC algorithm has a good resolution because of using subspace techniques consisting of a signal subspace and a noise subspace. The processor capability of drone system is required low power consumption and low computation complexity because it uses a microprocessor. If the drone system has a lot of computation complexity, the desired signal cannot be estimated. This paper study a method estimating the desired signal with a simple calculation. The proposed method is updated weight by the covariance matrix of MVDR algorithm. Through simulation, we analyse performance by comparing MVDR, MUSIC and the proposed method. In the simulation results, the proposed method is the same as the MUSIC algorithm in direction of arrival estimation. Since the proposed method has no subspace, it reduces computational complexity than MUSIC algorithm. The desired signal estimation of the proposed method is superior to the MVDR algorithm.

A Novel DOA Estimation Method for Wideband Signals

2011 ◽  
Vol 403-408 ◽  
pp. 2861-2865
Author(s):  
Fu Gang Liu ◽  
Ming Diao
Keyword(s):  
Performance Improvement ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Bias ◽  
Wideband Signals ◽  
Significant Performance ◽  
Simulation Results ◽  
The Impact ◽  
Real Time Application ◽  
Conventional Algorithm

For direction of arrival (DOA) estimation of wideband signals, the traditional algorithms’ estimating accuracy and complexity were mainly affected by pre-estimation of DOA. By forming an angle set which elements were arithmetic progressions in the range of possible arriving angles, the algorithm used the new angle vector to replace the preliminary estimation of arriving angles. It can avoid the impact of pre-estimation bias on performance of DOA estimation and greatly reduce the amount of computation and the consumed time for DOA estimation to favor the real-time application of wideband DOA estimation. The simulation results showed that the proposed algorithm was able to provide significant performance improvement over the conventional algorithm.

scholarly journals Multi-DOA Estimation Based on the KR Image Tensor and Improved CNN

2021 ◽  
Author(s):  
Ye Yuan ◽  
Shuang Wu ◽  
Yong Yang ◽  
Naichang Yuan
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Estimation Method ◽  
Doa Estimation ◽  
Classification Problem ◽  
Estimation Accuracy ◽  
Training Procedure ◽  
Low Snr ◽  
Simulation Results ◽  
Label Strategy

Abstract In this paper, we propose an improved convolutional neural network (CNN) to solve the multi-DOA estimation problem. We use Khatri-Rao (KR) product to obtain the KR image tensor of covariance matrix and use the proposed estimation CNN to process the tensor. In order to increase the generalization of the proposed CNN and adapt the multi-label classification problem, we use the curriculum learning scheme (CLS) and partial label strategy (PLS) to develop an efficient training procedure. We implement several experiments to demonstrate the satisfying performance of the proposed estimation method. The simulation results show that our proposed method can finish the high resolution multi-DOA estimation use only a few sensors. Furthermore, the proposed method can obtain high estimation accuracy under low SNR situations and use fewer snapshots.

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