Detection Algorithm of Maneuvering Target Based on Matched Fourier Transform

2018 ◽  
Author(s):  
Baofeng Guo ◽  
Huixian Sun ◽  
Wenhua Hu ◽  
Ning Han ◽  
Huiyan Zeng ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Detection Algorithm ◽  
Maneuvering Target

scholarly journals High-Speed Target Detection Algorithm Based on Sparse Fourier Transform

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 37828-37836 ◽  
Author(s):  
Cunsuo Pang ◽  
Shengheng Liu ◽  
Yan Han
Keyword(s):  
Fourier Transform ◽  
Target Detection ◽  
High Speed ◽  
Detection Algorithm

scholarly journals An Inverse Synthetic Aperture Ladar Imaging Algorithm of Maneuvering Target Based on Integral Cubic Phase Function-Fractional Fourier Transform

Electronics ◽  
2018 ◽  
Vol 7 (8) ◽  
pp. 148 ◽  
Author(s):  
Yakun Lv ◽  
Yanhong Wu ◽  
Hongyan Wang ◽  
Lei Qiu ◽  
Jiawei Jiang ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Phase Function ◽  
Fractional Fourier Transform ◽  
Doppler Frequency ◽  
Synthetic Aperture ◽  
Cubic Phase ◽  
Echo Signal ◽  
Imaging Algorithm ◽  
Maneuvering Target ◽  
Cubic Phase Function

When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed in this paper. The accurate ISAL echo signal model is established for a space maneuvering target that quickly approximates the uniform acceleration motion. On this basis, the chirp rate of the echo signal is quickly estimated by using the ICPF algorithm, which uses the non-uniform fast Fourier transform (NUFFT) method for fast calculations. At the best rotation angle, the range compression is realized by FRFT and the range dispersion is eliminated. After motion compensation, separation imaging of strong and weak scattering points is realized by using ICPF-FRFT and CLEAN technique and the azimuth defocusing problem is solved. The effectiveness of the proposed method is verified by a simulation experiment of an aircraft scattering point model and real data.

scholarly journals Low-Complexity MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4295 ◽  
Author(s):  
Bong-seok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Continuous Wave ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Field Of View ◽  
Music Algorithm ◽  
Trade Offs

This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30°, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment.

Track Health Monitoring Using Wavelets

2010 ◽  
Author(s):  
Brad M. Hopkins ◽  
Saied Taheri
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Defect Detection ◽  
Health Monitoring ◽  
Finite Energy ◽  
Detection Algorithm ◽  
Transient Signal ◽  
Vertical Acceleration ◽  
Typical Day ◽  
The Fourier Transform

This paper presents a defect detection algorithm for rail health monitoring that could potentially be used with limited bogie. Current wheel and track monitoring requires expensive track instrumentation and/or time consuming operation of railway monitoring vehicles. The proposed health monitoring algorithm can potentially be used with a portable data acquisition system that can be relocated from train to train to monitor and diagnose the conditions of the track as a train is driven during typical day-to-day operation. The algorithm processes the data using wavelets and is able to locate defects and provide information that may help to distinguish between various types of rail defects. In recent years, wavelets have been used extensively in signal processing because of their ability to analyze a signal simultaneously in the time and frequency domains. The Fourier transform has been used traditionally in signal processing to locate dominant frequencies in a signal, but it is unable to provide time localization of those frequencies. Unlike the Fourier transform, the wavelet transform uses a set of basis functions with finite energy, which is advantageous for detecting the irregular events that may show up in a transient signal. The wavelets used in the proposed signal processing routine were chosen for optimal signal decomposition through consideration of the signals that are likely to be generated from common rail and wheel defects, including rail cracks, squats, corrugation, and, wheel out-of-rounds. A sample accelerometer signal was generated from information found in existing literature and was then processed using the proposed defect detection algorithm. Results show the potential of this algorithm to locate and diagnose defects from limited bogie vertical acceleration data. This study is intended to present a proof-of-concept for the proposed defect detection algorithm, providing a basis for which a more comprehensive defect detection and diagnosis algorithm can be developed.

scholarly journals A Novel Algorithm for Fast DC Electric Arc Detection

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 288
Author(s):  
Michał Dołęgowski ◽  
Mirosław Szmajda
Keyword(s):  
Fourier Transform ◽  
Power Systems ◽  
Test Bench ◽  
Detection Algorithm ◽  
Electric Arc ◽  
Electric Load ◽  
Dc Voltage ◽  
Dc Power ◽  
Over Time ◽  
Novel Algorithm

Electric arcing is a common problem in DC power systems. To overcome this problem, the electric arc detection algorithm has been developed as a faster alternative to existing algorithms. The following issues are addressed in this paper: The calculation of the proposed algorithm of incremental decomposition of the signal over time; the computational complexity of Fast Fourier Transform (FFT) and the incremental decomposition; the test bench used to measure electric arcs at given parameters; the analysis of measurements using FFT; and the analysis of measurements using incremental decomposition. The parameters are the DC voltage, electric load, and width of the gap between electrodes. The results showed that the proposed algorithm allows for a faster calculation—about seven times faster than FFT—and cheaper implementation in electric arc detection devices than FFT.

scholarly journals Statistical Analysis of Target Detection using TRTSGRFT

2019 ◽  
Vol 8 (3) ◽  
pp. 6570-6573
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Statistical Analysis ◽  
Target Detection ◽  
Computational Cost ◽  
Doppler Frequency ◽  
Maneuvering Target ◽  
Novel Method ◽  
Range Migration ◽  
Motion Parameters

This paper proposes novel methodology for target detection and motion parameter estimation for a maneuvering target. Noise like interference may inculcate few difficulties such as Range Migration (RM) and Doppler Frequency Migration (DFM). This paper proposes a novel method to overcome the issue. The method is to use Time Reversing Transform (TRT) and special generalized Radon Fourier transform (SGRFT), i.e., TRT-SGRFT. TRT separates the motion parameters and reduces the clutter. Then the SGRFT operation is employed to estimate part of the motion parameters. This method ensures a good tradeoff between the computational cost and estimation performance. Finally, simulations results are discussed to demonstrate the numerical results.

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