scholarly journals Performance Analysis of Interferometer Direction of Arrival Estimation under Frequency Mismatch of Array Manifold: DOA of Frequency Hopping Signal

2020 ◽  
Vol 10 (7) ◽  
pp. 2331
Author(s):  
Chan-Bin Ko ◽  
Joon-Ho Lee
Keyword(s):  
Performance Analysis ◽  
Estimation Error ◽  
Elevation Angle ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Frequency Hopping ◽  
Azimuth Angle ◽  
Direction Of Arrival Estimation ◽  
Actual Frequency ◽  
Frequency Mismatch

We consider the direction of arrival (DOA) estimation of the frequency hopping (FH) signal. The frequency hopping (FH) signal has been widely used for communication to control UAVs. Since the frequency of the FH signal is continuously changing, a mismatch may occur between the actual frequency of the received signal and the nominal frequency of the array manifold. In this paper, the azimuth and elevation estimation error in DOA estimation due to frequency mismatch are analytically derived. It is shown that the azimuth error is equal to zero and that elevation error depends on true elevation angle of the incident signal, rather than the true azimuth angle of the incident signal. The elevation error is also dependent on the actual frequency and the nominal frequency.

scholarly journals Direction of Arrival Estimation in the presence of Scatterer in noisy environment

2017 ◽  
Vol 6 (3) ◽  
pp. 33
Author(s):  
T. Aslam ◽  
I. Ahmed ◽  
M. I. Aslam ◽  
S. M. U. Ali ◽  
T. Malik
Keyword(s):  
Gaussian Noise ◽  
Signal To Noise Ratio ◽  
Estimation Error ◽  
Additive White Gaussian Noise ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Noisy Environment ◽  
Signal To Noise ◽  
Incoming Wave

We present an algorithm to estimate direction of arrival (DOA) of an incoming wave received at an array antenna in the scenario where the incoming wave is contaminated by the additive white Gaussian noise and scattered by arbitrary shaped 3D scatterer(s). We present different simulation examples to show the validity of the proposed method. It is observed that the proposed algorithm is capable of closely estimating the DOA of an incoming wave irrespective of the shape of the scatterer provided the decision is made over multiple iterations. Moreover, presence of noise affects the estimate especially in the case of low signal-to-noise ratio (SNR) that gives a relatively large estimation error. However, for larger SNR the DOA estimation is primarily dependent on the scatterer only.

Neural network-aided sparse convex optimization algorithm for fast DOA estimation

2021 ◽  
pp. 014233122110490
Author(s):  
Jingyu Cong ◽  
Xianpeng Wang ◽  
Liangtian Wan ◽  
Mengxing Huang
Keyword(s):  
Neural Network ◽  
Convex Optimization ◽  
Optimization Algorithm ◽  
Estimation Error ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Variable Number ◽  
Vector Model ◽  
Direction Of Arrival Estimation ◽  
Toeplitz Structure

In this paper, a fast sparse convex optimization algorithm based on a neural network is proposed to improve the direction of arrival estimation. First, a fast [Formula: see text]-sparse representation of the array covariance vector model based on the Hermitian Toeplitz structure of array covariance is established to reduce computational complexity in data dimension and variable number. Then, the estimation error upper bound problem is investigated, and a neural network-aided coefficient selection method is developed. The direction of arrival estimation problem is solved through spectral peak search. Finally, the algorithm is extended to the case of off-grid error. The algorithm’s advantages in accuracy, calculation speed and robustness is verified by the simulations.

scholarly journals A Novel Virtual Time Reversal Method for Passive Direction of Arrival Estimation

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yongqing Fu ◽  
Wei Liu ◽  
Ruijie Bai ◽  
Jingrui Li ◽  
Jinlin Wang
Keyword(s):  
Time Reversal ◽  
Mathematical Proof ◽  
Elevation Angle ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Azimuth Angle ◽  
Electromagnetic Signal ◽  
Low Snr ◽  
Implementation Scheme ◽  
Virtual Time

The paper presents a new method to estimate the two-dimensional (2D) direction of arrival (DOA) (the azimuth angle and the elevation angle) of electromagnetic signal emitted from a single communication station. This method is passive and accurate in the case of low signal-noise ratio (SNR) based on the virtual time reversal (VTR) theory. In order to illustrate its principle, the theoretical formulas of VTR direction finding with uniform circular array (UCA) are derived firstly. Based on these formulas, the implementation scheme for estimating azimuth angle and elevation angle passively is then provided. In the derivation, the strict mathematical proof for compressing planar search area to a curve line is proposed, reducing the complexity of VTR algorithm greatly. Finally, the simulation experiments are performed to validate the performance of VTR algorithm. The results show that the VTR method is effective and it delivers accurate DOA estimation in the case of low SNR.

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

scholarly journals A Direction-of-Arrival Estimation Algorithm Based on Compressed Sensing and Density-Based Spatial Clustering and Its Application in Signal Processing of MEMS Vector Hydrophone

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2191
Author(s):  
Huichao Yan ◽  
Ting Chen ◽  
Peng Wang ◽  
Linmei Zhang ◽  
Rong Cheng ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Spatial Clustering ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Cluster Center ◽  
Direction Of Arrival Estimation ◽  
Vector Hydrophone ◽  
Regularization Parameters ◽  
Selection Of

Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimation method based on compressed sensing (CS) is a new method proposed in recent years. It has received widespread attention because it can realize the direction-of-arrival estimation under small snapshots. However, this method will cause serious distortion in a strong noise environment. To solve this problem, this paper proposes a DOA estimation algorithm based on the principle of CS and density-based spatial clustering (DBSCAN). First of all, in order to make the estimation accuracy higher, this paper selects a signal reconstruction strategy based on the basis pursuit de-noising (BPDN). In response to the challenge of the selection of regularization parameters in this strategy, the power spectrum entropy is proposed to characterize the noise intensity of the signal, so as to provide reasonable suggestions for the selection of regularization parameters; Then, this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis, so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate; Finally, calculate the cluster center value of each cluster, the number of clusters is the number of signal sources, and the cluster center value is the final DOA estimate. The proposed method is applied to the simulation experiment and the micro electro mechanical system (MEMS) vector hydrophone lake test experiment, and they are proved that the proposed method can obtain good results of DOA estimation under the conditions of small snapshots and low signal-to-noise ratio (SNR).

Direction of Arrival Estimation with Compact Array Antennas

2009 ◽  
pp. 201-216
Author(s):  
Eddy Taillefer ◽  
Jun Cheng ◽  
Takashi Ohira
Keyword(s):  
Single Port ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Signal Classification ◽  
Direction Of Arrival Estimation ◽  
Multiple Signal Classification ◽  
Array Antennas ◽  
Power Pattern ◽  
Parasitic Array ◽  
Compact Array

This chapter presents direction of arrival (DoA) estimation with a compact array antenna using methods based on reactance switching. The compact array is the single-port electronically steerable parasitic array radiator (Espar) antenna. The antenna beam pattern is controlled though parasitic elements loaded with reactances. DoA estimation using an Espar antenna is proposed with the power pattern cross correlation (PPCC), reactance-domain (RD) multiple signal classification (MUSIC), and, RD estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms. The three methods exploit the reactance diversity provided by an Espar antenna to correlate different antenna output signals measured at different times and for different reactance values. The authors hope that this chapter allows the researchers to appreciate the issues that may be encountered in the implementation of direction-finding application with a single-port compact array like the Espar antenna.

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