Implementation of Unitary Music Algorithm Using Xilinx System Generator

2013 ◽  
Vol 748 ◽  
pp. 629-633
Author(s):  
Mer Wan Lounici ◽  
Xiao Ming Luan
Keyword(s):  
Super Resolution ◽  
Eigenvalue Decomposition ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
System Generator ◽  
Resolution Capability ◽  
Coordinate Rotation ◽  
Field Programmable ◽  
Computer Based ◽  
Xilinx System Generator

The MUltiple SIgnal Classification MUSIC algorithm is a kind of DOA (Direction Of Arrival) estimation technique based on eigenvalue decomposition, which is also called subspace-based method [5]. In addition of its super resolution capability, MUSIC is very suitable for integration on logic circuit devices such as FPGAs (Field Programmable Gate Array).this paper proposes an implementation of unitary MUSIC algorithm using Xilinx System Generator (XSG). The design proposed uses CORDIC (COordinate Rotation DIgital Computer) -based Triangular Systolic Array for QR- decomposition to deal with EVD (eigenvalue decomposition). The MUSIC spectrum is computed with spatial DFT (Discrete Fourier Transform) using FFT block offered by Simulink- Xilinx blockset library. The performance of eight elements antenna array system was obtained and discussed.

Implementation of RGB to HSV Color Space Conversion with Xilinx System Generator

2013 ◽  
Vol 816-817 ◽  
pp. 527-534 ◽  
Author(s):  
Long Wen ◽  
Cheng Xu ◽  
Tao Li ◽  
Zheng Tian
Keyword(s):  
Color Space ◽  
Design Tool ◽  
Color Model ◽  
Hsv Color Space ◽  
System Generator ◽  
Color Space Conversion ◽  
Field Programmable ◽  
C Program ◽  
Xilinx System Generator ◽  
Program Experiment

The HSV (Hue, Saturation, and Value) color model is more intuitive than the RGB color model and widely used in color recognition and color space segmentation. Currently as the requirements of high processing speed and special applications need to realize RGB to HSV color space conversion, in this paper a new Field Programmable Gate Array (FPGA) architecture named RGB2HSV module was developed via an accurate and visible FPGA implementation method in use of Xilinx System Generator (XSG). XSG is a design tool in Simulink of MATLAB which accelerates design by providing access to highly parameterized intellectual blockset for Xilinx FPGA. In this paper simulation test images were used to measure the deviation and the time consume by the RGB2HSV module and relevant C program. Experiment shows that the maximum frequency can reach 121.433MHz and lower deviation was achieved in Xilinx Zynq xc7z020 device. The full-pipelined and parallel RGB2HSV module had been adapted in order to speed up the RGB to HSV color space conversion and took as much as 87% less than that of C program in our experiment.

scholarly journals Control neuronal de un sistema de equilibrio (péndulo invertido) en dispositivos lógicos programables

2017 ◽  
Vol 4 (2) ◽  
pp. 40
Author(s):  
Johnny Omar Medina Durán ◽  
Norbey Chinchilla Herrera ◽  
Ruby Daniela Vargas Quintero ◽  
Yesenia Restrepo Chaustre
Keyword(s):  
Field Programmable Gate Array ◽  
System Generator ◽  
Field Programmable ◽  
Gate Array ◽  
Xilinx System Generator ◽  
La Red

Este trabajo presenta la implementación de una Red Neuronal FeedFoward para el control de equilibrio de un sistema sobre dos ruedas (péndulo invertido), en una tarjeta de desarrollo Nexys 2 de Digilent, que contiene una FPGA (Field Programmable Gate Array) XC3S500E. La herramienta utilizada para la creación, entrenamiento y simulación de la red neuronal fue la NNTool de Matlab. El algoritmo neuronal fue traducido a un modelo realizable en hardware, mediante diagramas de bloques, desarrollados con las herramientas Simulink y Xilinx System Generator (XSG). La validación de la red neuronal se realiza en un prototipo de equilibrio sobre dos ruedas. Este sistema tiene una unidad de medida inercial (IMU 6dof- MPU 6050), que incluyen un acelerómetro y un giroscopio de tres ejes cada uno, y 2 motorreductores con encoder magnético, utilizados como actuadores.

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 Reduced-Complexity Direction of Arrival Estimation Using Real-Valued Computation with Arbitrary Array Configurations

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Feng-Gang Yan ◽  
Jun Wang ◽  
Shuai Liu ◽  
Yi Shen ◽  
Ming Jin
Keyword(s):  
State Of The Art ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Eigenvalue Decomposition ◽  
Music Algorithm ◽  
New Approach ◽  
Multiple Signal Classification ◽  
Wide Range ◽  
Complexity Algorithm

A low-complexity algorithm is presented to dramatically reduce the complexity of the multiple signal classification (MUSIC) algorithm for direction of arrival (DOA) estimation, in which both tasks of eigenvalue decomposition (EVD) and spectral search are implemented with efficient real-valued computations, leading to about 75% complexity reduction as compared to the standard MUSIC. Furthermore, the proposed technique has no dependence on array configurations and is hence suitable for arbitrary array geometries, which shows a significant implementation advantage over most state-of-the-art unitary estimators including unitary MUSIC (U-MUSIC). Numerical simulations over a wide range of scenarios are conducted to show the performance of the new technique, which demonstrates that with a significantly reduced computational complexity, the new approach is able to provide a close accuracy to the standard MUSIC.

scholarly journals Two-Dimensional Direction-of-Arrival Estimation for Trilinear Decomposition-Based Monostatic Cross MIMO Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Fangqing Wen ◽  
Gong Zhang
Keyword(s):  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Mimo Radar ◽  
Eigenvalue Decomposition ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Trilinear Decomposition ◽  
Signal Covariance Matrix

A low complexity monostatic cross multiple-in multiple-out (MIMO) radar scheme is proposed in this paper. The minimum-redundancy linear array (MRLA) is introduced in the cross radar to improve the efficiency of the array elements. The two-dimensional direction-of-arrival (DOA) estimation problem links to the trilinear model, which automatically pairs the estimated two-dimensional angles, requiring neither eigenvalue decomposition of received signal covariance matrix nor spectral peak searching. The proposed scheme performs better than the uniform linear arrays (ULA) configuration under the same conditions, and the proposed algorithm has less computational complexity than that of multiple signal classification (MUSIC) algorithm. Simulation results show the effectiveness of our scheme.

scholarly journals A Local TR-MUSIC Algorithm for Damage Imaging of Aircraft Structures

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3334
Author(s):  
Shilei Fan ◽  
Aijia Zhang ◽  
Hu Sun ◽  
Fenglin Yun
Keyword(s):  
Image Quality ◽  
Time Window ◽  
Eigenvalue Decomposition ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Structural Space ◽  
Damage Imaging ◽  
Local Space ◽  
Plate Type ◽  
Space Spectrum

Lamb wave-based damage imaging is a promising technique for aircraft structural health monitoring, as enhancing the resolution of damage detection is a persistent challenge. In this paper, a damage imaging technique based on the Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) algorithm is developed to detect damage in plate-type structures. In the TR-MUSIC algorithm, a transfer matrix is first established by exciting and sensing signals. A TR operator is constructed for eigenvalue decomposition to divide the data space into signal and noise subspaces. The structural space spectrum of the algorithm is calculated based on the orthogonality of the two subspaces. A local TR-MUSIC algorithm is proposed to enhance the image quality of multiple damages by using a moving time window to establish the local space spectrum at different times or different distances. The multidamage detection capability of the proposed enhanced TR-MUSIC algorithm is verified by simulations and experiments. The results reveal that the local TR-MUSIC algorithm can not only effectively detect multiple damages in plate-type structures with good image quality but also has a superresolution ability for detecting damage with distances smaller than half the wavelength.

Study on Resolution Capability of Beam Space MUSIC Estimation Algorithm

2014 ◽  
Vol 945-949 ◽  
pp. 2106-2110
Author(s):  
Hao Zhou ◽  
Zhi Jie Huo
Keyword(s):  
Estimation Algorithm ◽  
Signal Classification ◽  
Beam Forming ◽  
Music Algorithm ◽  
Correlated Sources ◽  
Element Space ◽  
Computation Cost ◽  
Multiple Signal Classification ◽  
Resolution Capability ◽  
Sonar Systems

Hydrophone arrays are generally used in modern sonar systems in which beam forming plays an important role. This paper analyzes the beam space MUSIC (multiple signal classification) algorithm for the weakly correlated sources according to changes in the statistical properties of signal and noise, then estimates the azimuth of multi-sources using array element space MUSIC algorithm and beam space MUSIC algorithm accurately, respectively. Finally, problems such as the computation cost of the algorithms, SNR resolution threshold and estimation deviation are discussed based on simulation tests. A conclusion could be drawn that beam space MUSIC algorithm is an effective way to resolve multiple targets in small angle domain.

scholarly journals High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4018
Author(s):  
Bong-seok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
High Efficiency ◽  
Continuous Wave ◽  
Super Resolution ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Fmcw Radar ◽  
Similar Performance ◽  
Average Complexity ◽  
Resolution Algorithm ◽  
And Performance

This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. The proposed algorithm employs the reduced samples by the estimated distance by FFT as input to the super resolution algorithm instead of the maximum number of samples set by the maximum detectable distance. By doing so, the proposed algorithm achieves the similar performance of the conventional multiple signal classification algorithm (MUSIC), which is a representative of the super resolution algorithms while the performance does not degrade. Simulation results demonstrate the feasibility and performance improvement provided by the proposed algorithm; that is, the proposed algorithm achieves average complexity reduction of 88% compared to the conventional MUSIC algorithm while achieving its similar performance. Moreover, the improvement provided by the proposed algorithm was verified in practical conditions, as evidenced by our experimental results.

scholarly journals PUMA Applied to Time Delay Estimation for Processing GPR Data over Debonded Pavement Structures

2021 ◽  
Vol 13 (17) ◽  
pp. 3456
Author(s):  
Bachir Tchana Tankeu ◽  
Vincent Baltazart ◽  
Yide Wang ◽  
David Guilbert
Keyword(s):  
Time Delay ◽  
Singular Vector ◽  
Super Resolution ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Computational Time ◽  
Music Algorithm ◽  
Resolution Capability ◽  
Pavement Structures ◽  
Ground Penetrating

In this paper, principal-singular-vector utilization for modal analysis (PUMA) was adapted to perform time delay estimation on ground-penetrating radar (GPR) data by taking into account the shape of the transmitted GPR signal. The super-resolution capability of PUMA was used to separate overlapping backscattered echoes from a layered pavement structure with some embedded debondings. The well-known root-MUSIC algorithm was selected as a benchmark for performance assessment. The simulation results showed that the proposed PUMA performs very well, especially in the case where the sources are totally coherent, and it requires much less computational time than the root-MUSIC algorithm.

scholarly journals Super-Resolution Range and Velocity Estimations for SFA-OFDM Radar

2022 ◽  
Vol 14 (2) ◽  
pp. 278
Author(s):  
Zhixing Liu ◽  
Yinghui Quan ◽  
Yaojun Wu ◽  
Mengdao Xing
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Linear Array ◽  
Super Resolution ◽  
Music Algorithm ◽  
Excellent Performance ◽  
Multiple Signal Classification ◽  
Parameter Estimations ◽  
Coherent Integration ◽  
Ofdm Signal ◽  
Frequency Agile

Sparse frequency agile orthogonal frequency division multiplexing (SFA-OFDM) signal brings excellent performance to electronic counter-countermeasures (ECCM) and reduces the complexity of the radar system. However, frequency agility makes coherent processing a much more challenging task for the radar, which leads to the discontinuity of the echo phase in a coherent processing interval (CPI), so the fast Fourier transform (FFT)-based method is no longer a valid way to complete the coherent integration. To overcome this problem, we proposed a novel scheme to estimate both super-resolution range and velocity. The subcarriers of each pulse are firstly synthesized in time domain. Then, the range and velocity estimations for the SFA-OFDM radar are regarded as the parameter estimations of a linear array. Finally, both the super-resolution range and velocity are obtained by exploiting the multiple signal classification (MUSIC) algorithm. Simulation results are provided to demonstrate the effectiveness of the proposed method.

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