scholarly journals Joint DOA and Polarization Estimation for Unequal Power Sources

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qingyuan Fang ◽  
Yong Han ◽  
Ming Jin ◽  
Wenyi Dong
Keyword(s):  
Estimation Method ◽  
Estimation Methods ◽  
Invariance Property ◽  
Music Algorithm ◽  
Power Sources ◽  
Multiple Signal Classification ◽  
Power Difference ◽  
Joint Direction ◽  
Polarization Estimation ◽  
Cramer Rao Bound

For most joint direction of arrival (DOA) and polarization estimation methods, the performances of proposed methods in dealing with unequal power sources are not discussed. However, sources with unequal powers apparently exist widely in actual applications. In this study, we propose a joint DOA and polarization estimation method for unequal power sources by utilizing the invariance property of noise subspace (IPNS) to the power of sources. This work extends the IPNS method to the dual polarized antenna array for joint DOA and polarization estimation. Moreover, we theoretically prove that the IPNS remains valid even when the sources are correlated. The computer simulations illustrate that the proposed method can effectively estimate the DOA and polarization parameters as the power difference between sources increases, as opposed to the polarimetric multiple signal classification (MUSIC) algorithm, which suffers from degradation in resolution probability. In addition, the performances of the proposed method are provided, as well the Cramer Rao Bound (CRB), which show approximate performance as the polarimetric MUSIC algorithm.

scholarly journals Polarization and DOA Estimation Based on Dual-Polarized Conformal Array

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Chao Liu ◽  
Shuai Xiang ◽  
Liangfeng Xu ◽  
Zhengfei Fang
Keyword(s):  
Doa Estimation ◽  
Signal Classification ◽  
Orthogonal Polarization ◽  
Coherent Signals ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Polarization Signal ◽  
Conformal Array ◽  
Dual Polarized ◽  
Cramer Rao Bound

A dual-polarized multiple signal classification (DP-MUSIC) algorithm is presented to estimate the arrival directions and polarizations for a dual-polarized conformal array. Each polarization signal is decomposed into two orthogonal polarization components, which are considered to be a pair of coherent signals coming from the same direction but different polarization. The polarization parameters are modeled as the equivalent coherence coefficients of the orthogonal polarization components. Then, the method of decoherence can be used to decouple the information of polarization states and signal angles. After that, the direction of arrival (DOA) and polarization parameters can be estimated by the DP-MUSIC algorithm. Moreover, the angles of incident direction are re-estimated, which greatly improves the accuracy of DOA estimation. The Cramer–Rao bound (CRB) is derived and the effectiveness of the proposed algorithm is verified by Monte Carlo simulations.

Frequency Spectrum Estimate Based on Decomposed FLOC Matrix under Stable Distribution Noise

2014 ◽  
Vol 556-562 ◽  
pp. 4563-4567 ◽  
Author(s):  
Hai Bin Wang ◽  
Jun Bo Long ◽  
You Xue Zhou ◽  
Dai Feng Zha
Keyword(s):  
Frequency Spectrum ◽  
Stable Distribution ◽  
Estimation Method ◽  
Estimation Methods ◽  
Spectrum Estimation ◽  
Complex Environment ◽  
Multiple Signal Classification ◽  
Second Order Statistics ◽  
Estimate Method ◽  
Conventional Algorithm

The radar work in a complex environment where the noise has very strong pulse, the noise can be described by stable distribution. The conventional spectrum estimation method based on second order statistics is reasonable in many cases, however, the performance of the conventional algorithm degenerate in stable distribution environment. We propose three new frequency spectrum estimate method with Fractional lower order covariance (FLOC), FLOC-Pisarenko method, FLOC-Esprit method and FLOC multiple signal classification (FLOC-MUSIC) method. The conventional spectrum estimation methods with three proposed methods under Gaussian noise and stable distribution are compared in this paper, simulations show that the conventional methods degenerate, but the proposed algorithms can work better in stable distribution environment, and are robust.

UM2000 Spectrum Estimation Using Multiple Signal Classification Method

2013 ◽  
Vol 734-737 ◽  
pp. 2622-2629
Author(s):  
Shen Liu ◽  
Fu Ping Wang ◽  
Xiu Cheng Liu
Keyword(s):  
Minimum Description Length ◽  
Spectral Estimation ◽  
Frequency Discrimination ◽  
Frequency Resolution ◽  
Estimation Methods ◽  
Signal Spectrum ◽  
Spectrum Estimation ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Signal Simulation

This paper focused on UM2000 signal spectrum estimation using MUSIC algorithm. Because of the limitation of data window length, traditional frequency discrimination methods fail to meet the requirement of high frequency resolution. In this paper, the influence of SNR on MUSIC spectrum estimation is analyzed and MDL (minimum description length) principle is used to determine the dimension of the signal. Simulation results based on several other modern spectral estimation methods are also presented and compared with that of MUSIC method, from which the superiority of MUSIC method is verified.

Harmonic Frequency Estimation Based on Modified-MUSIC Algorithm in Power System

2015 ◽  
Vol 9 (1) ◽  
pp. 38-42 ◽  
Author(s):  
Xiangwen Sun ◽  
Ligong Sun
Keyword(s):  
Frequency Estimation ◽  
Estimation Method ◽  
Super Resolution ◽  
Small Data ◽  
Music Algorithm ◽  
Harmonic Frequency ◽  
Multiple Signal Classification ◽  
Analysis Techniques ◽  
Resolution Algorithm ◽  
Data Length

This paper presents a new harmonics frequency estimation method. Unlike the conventional harmonic frequency estimation method (fast Fourier transform), the new algorithm is based on spectrum analysis techniques often used to estimate the direction of angle; the most popular is the multiple signal classification (MUSIC) algorithm. The drawbacks of MUSIC algorithm are concluded. Improved-MUSIC approximation algorithm is introduced and compared with FFT based on algorithm for harmonic frequency estimation. Theoretical analysis and simulations show this algorithm is a super- resolution algorithm with small data length.

scholarly journals Uni-Vector-Sensor Dimensionality Reduction MUSIC Algorithm for DOA and Polarization Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Lanmei Wang ◽  
Le Yang ◽  
Guibao Wang ◽  
Zhihai Chen ◽  
Minggao Zou
Keyword(s):  
Dimensionality Reduction ◽  
Polarization Function ◽  
Music Algorithm ◽  
Arrival Angle ◽  
Multiple Signal Classification ◽  
Vector Sensor ◽  
Angle Function ◽  
Polarization Estimation ◽  
Function Vector ◽  
Function Matrix

This paper addresses the problem of multiple signal classification- (MUSIC-) based direction of arrival (DOA) and polarization estimation and proposes a new dimensionality reduction MUSIC (DR-MUSIC) algorithm. Uni-vector-sensor MUSIC algorithm provides estimation for DOA and polarization; accordingly, a four-dimensional peak search is required, which hence incurs vast amount of computation. In the proposed DR-MUSIC method, the signal steering vector is expressed in the product form of arrival angle function matrix and polarization function vector. The MUSIC joint spectrum is converted to the form of Rayleigh-Ritz ratio by using the feature where the 2-norm of polarization function vector is constant. A four-dimensional MUSIC search reduced the dimension to two two-dimensional searches and the amount of computation is greatly decreased. The theoretical analysis and simulation results have verified the effectiveness of the proposed algorithm.

scholarly journals A Sensor-Driven Analysis of Distributed Direction Finding Systems Based on UAV Swarms

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2659 ◽  
Author(s):  
Zhong Chen ◽  
Shihyuan Yeh ◽  
Jean-Francois Chamberland ◽  
Gregory H. Huff
Keyword(s):  
Data Collection ◽  
Antenna Arrays ◽  
Collection System ◽  
Music Algorithm ◽  
System Framework ◽  
Data Collection System ◽  
Multiple Signal Classification ◽  
Source Case ◽  
Aerial Vehicle ◽  
Cramer Rao Bound

This paper reports on the research of factors that impact the accuracy and efficiency of an unmanned aerial vehicle (UAV) based radio frequency (RF) and microwave data collection system. The swarming UAVs (agents) can be utilized to create micro-UAV swarm-based (MUSB) aperiodic antenna arrays that reduce angle ambiguity and improve convergence in sub-space direction-of-arrival (DOA) techniques. A mathematical data model is addressed in this paper to demonstrate fundamental properties of MUSB antenna arrays and study the performance of the data collection system framework. The Cramer–Rao bound (CRB) associated with two-dimensional (2D) DOAs of sources in the presence of sensor gain and phase coefficient is derived. The single-source case is studied in detail. The vector-space of emitters is exploited and the iterative-MUSIC (multiple signal classification) algorithm is created to estimate 2D DOAs of emitters. Numerical examples and practical measurements are provided to demonstrate the feasibility of the proposed MUSB data collection system framework using iterative-MUSIC algorithm and benchmark theoretical expectations.

Interference Localization via Direction of Arrival Estimation for Satellite with Planar Array

2014 ◽  
Vol 1049-1050 ◽  
pp. 1788-1791
Author(s):  
Xiao Feng Qiu ◽  
Xiao Fei Zhang
Keyword(s):  
Computational Cost ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Music Algorithm ◽  
Angle Estimation ◽  
Multiple Signal Classification ◽  
Estimation Performance ◽  
Planar Array ◽  
Esprit Algorithm

This paper presents the model of satellite planar array, and interference localization via direction of arrival (DOA) estimation. We derive a dimension reduction DOA estimaton algorithm therein. The proposed algorithm, which only requires a one-dimensional local searching, can avoid the high computational cost within two-dimensional multiple signal classification (2D-MUSIC) algorithm. We illustrate that the proposed algorithm has better angle estimation performance than estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm, and has very close angle estimation performance to 2D-MUSIC algorithm. Furthermore, our algorithm requires no extra pairing. Simulation results present the usefulness of our algorithm.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

scholarly journals Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 26
Author(s):  
David González-Ortega ◽  
Francisco Javier Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Virtual Reality ◽  
Comparative Analysis ◽  
Driving Simulator ◽  
Estimation Method ◽  
Estimation Methods ◽  
Gaze Estimation ◽  
Driving Simulators ◽  
Oculus Rift ◽  
Gaze Patterns ◽  
And Performance

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.

scholarly journals Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Estimation Method ◽  
Absolute Error ◽  
Large Error ◽  
Estimation Methods ◽  
Height Estimation ◽  
Building Height ◽  
Remote Sensing Imagery ◽  
High Resolution Imagery

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.

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