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.

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.

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.

Performance Optimization of DOA Estimation in Non-Uniform Linear Antenna Array by PSO Algorithm

2014 ◽  
Vol 490-491 ◽  
pp. 451-455
Author(s):  
Hui Lian Han ◽  
Liang Tian Wan ◽  
Wei Jian Si
Keyword(s):  
Performance Optimization ◽  
Linear Array ◽  
Doa Estimation ◽  
Pso Algorithm ◽  
Music Algorithm ◽  
Uniform Linear Array ◽  
Multiple Signal Classification ◽  
Array Configuration ◽  
Strong Stabilization ◽  
Simple Processing

In order to estimate the coherent source, a modified multiple signal classification (MUSIC) algorithm is introduced. And a novel arrangement method for the non-uniform linear array by particle swarm optimization (PSO) algorithm is proposed. This method needs merely a signal source whose direction-of-arrival (DOA) has been exactly known. The proposed method has a simple processing and a strong stabilization. It could be applied to optimized arbitrary array configuration. The simulation verifies that the performance of DOA estimation is improved effectively, which has proved the validity of the proposed method.

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 Full snapshot reconstruction in hybrid architecture antenna arrays

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Maria Trigka ◽  
Christos Mavrokefalidis ◽  
Kostas Berberidis
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Communication Systems ◽  
Linear Array ◽  
Research Work ◽  
Hybrid Architecture ◽  
Angle Of Arrival ◽  
Music Algorithm ◽  
Array Structures ◽  
Signal Sources

AbstractIn the context of this research work, we study the so-called problem of full snapshot reconstruction in hybrid antenna array structures that are utilized in mmWave communication systems. It enables the recovery of the snapshots that would have been obtained if a conventional (non-hybrid) uniform linear antenna array was employed. The problem is considered at the receiver side where the hybrid architecture exploits in a novel way the antenna elements of a uniform linear array. To this end, the recommended scheme is properly designed so as to be applicable to overlapping and non-overlapping architectures. Moreover, the full snapshot recoverability is addressed for two cases, namely for time-varying and constant signal sources. Simulation results are also presented to illustrate the consistency between the theoretically predicted behaviors and the simulated results, and the performance of the proposed scheme in terms angle-of-arrival estimation, when compared to the conventional MUSIC algorithm and a recently proposed hybrid version of MUSIC (H-MUSIC).

scholarly journals Bearing and Range Estimation Algorithm for Buried Object in Underwater Acoustics

2009 ◽  
Vol 2009 ◽  
pp. 1-4
Author(s):  
Dong Han ◽  
Caroline Fossati ◽  
Salah Bourennane ◽  
Zineb Saidi
Keyword(s):  
Underwater Acoustics ◽  
Classical Model ◽  
Acoustic Scattering ◽  
Estimation Algorithm ◽  
Signal Classification ◽  
Music Algorithm ◽  
Range Estimation ◽  
Multiple Signal Classification ◽  
Buried Objects ◽  
Buried Object

A new algorithm which associates (Multiple Signal Classification) MUSIC with acoustic scattering model for bearing and range estimation is proposed. This algorithm takes into account the reflection and the refraction of wave in the interface of water-sediment in underwater acoustics. A new directional vector, which contains the Direction-Of-Arrival (DOA) of objects and objects-sensors distances, is used in MUSIC algorithm instead of classical model. The influence of the depth of buried objects is discussed. Finally, the numerical results are given in the case of buried cylindrical shells.

scholarly journals Fast Estimation Method of Space-Time Two-Dimensional Positioning Parameters Based on Hadamard Product

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Haiwen Li ◽  
Nae Zheng ◽  
Xiyu Song ◽  
Yinghua Tian
Keyword(s):  
Frequency Domain ◽  
Orthogonal Frequency Division Multiplexing ◽  
Hadamard Product ◽  
Estimation Method ◽  
Space Time ◽  
Joint Estimation ◽  
Two Dimensional ◽  
Music Algorithm ◽  
Fast Estimation ◽  
Response Vector

The estimation speed of positioning parameters determines the effectiveness of the positioning system. The time of arrival (TOA) and direction of arrival (DOA) parameters can be estimated by the space-time two-dimensional multiple signal classification (2D-MUSIC) algorithm for array antenna. However, this algorithm needs much time to complete the two-dimensional pseudo spectral peak search, which makes it difficult to apply in practice. Aiming at solving this problem, a fast estimation method of space-time two-dimensional positioning parameters based on Hadamard product is proposed in orthogonal frequency division multiplexing (OFDM) system, and the Cramer-Rao bound (CRB) is also presented. Firstly, according to the channel frequency domain response vector of each array, the channel frequency domain estimation vector is constructed using the Hadamard product form containing location information. Then, the autocorrelation matrix of the channel response vector for the extended array element in frequency domain and the noise subspace are calculated successively. Finally, by combining the closed-form solution and parameter pairing, the fast joint estimation for time delay and arrival direction is accomplished. The theoretical analysis and simulation results show that the proposed algorithm can significantly reduce the computational complexity and guarantee that the estimation accuracy is not only better than estimating signal parameters via rotational invariance techniques (ESPRIT) algorithm and 2D matrix pencil (MP) algorithm but also close to 2D-MUSIC algorithm. Moreover, the proposed algorithm also has certain adaptability to multipath environment and effectively improves the ability of fast acquisition of location parameters.

scholarly journals Two-Step Root-MUSIC for Direction of Arrival Estimation without EVD/SVD Computation

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Feng-Gang Yan ◽  
Shuai Liu ◽  
Jun Wang ◽  
Ming Jin
Keyword(s):  
Super Resolution ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Music Algorithm ◽  
Correlation Matrices ◽  
Noise Subspace ◽  
Using Data ◽  
Eigen Decomposition ◽  
Value Decomposition

Most popular techniques for super-resolution direction of arrival (DOA) estimation rely on an eigen-decomposition (EVD) or a singular value decomposition (SVD) computation to determine the signal/noise subspace, which is computationally expensive for real-time applications. A two-step root multiple signal classification (TS-root-MUSIC) algorithm is proposed to avoid the complex EVD/SVD computation using a uniform linear array (ULA) based on a mild assumption that the number of signals is less than half that of sensors. The ULA is divided into two subarrays, and three noise-free cross-correlation matrices are constructed using data collected by the two subarrays. A low-complexity linear operation is derived to obtain a rough noise subspace for a first-step DOA estimate. The performance is further enhanced in the second step by using the first-step result to renew the previous estimated noise subspace with a slightly increased complexity. The new technique can provide close root mean square error (RMSE) performance to root-MUSIC with reduced computational burden, which are verified by numerical simulations.

Super-Resolution Time-Delays Estimation in HF Channel Sounding Based on Chirp Sequence

2011 ◽  
Vol 204-210 ◽  
pp. 2133-2139
Author(s):  
Long Fei Fu ◽  
Gang Xin ◽  
Shui Lian Zhang
Keyword(s):  
Time Delay ◽  
Time Delays ◽  
Measurement Data ◽  
Super Resolution ◽  
Wide Band ◽  
Estimation Problem ◽  
Delay Model ◽  
Music Algorithm ◽  
Problem Of Time ◽  
Hf Channel

According to the characteristics of HF channel and chirp signal, an innovative multipath time-delay model of wide-band HF channel was proposed, by which the estimation problem of time-delay was converted into an estimation problem of spectrum.Then the MUSIC algorithm with super-resolution ability was applied to the problem above. The feasibility of estimating multipath time-delays based on single measurement data was deeply discussed. Meanwhile, the performance of applying MUSIC and root MUSIC algorithm to the model proposed in the paper was presented. The simulation results suggested that the method proposed in the paper owned super-resolution ability and robust in estimation of multipath time-delay.

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