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Micro-Doppler Signature Detection and Recognition of UAVs Based on omp algorithm

SENSORS 2023年第18期23卷 7922-7922页

作者： Fan, Shiqi Wu, Ziyan Xu, Wenqiang Zhu, Jiabao Tu, Gangyi Nanjing Univ Informat Sci & Technol Dept Elect & Informat Engn Nanjing 210044 Peoples R China

With the proliferation of unmanned aerial vehicles (UAVs) in both commercial and military use, the public is paying increasing attention to UAV identification and regulation. The micro-Doppler characteristics of a UAV can reflect its structure and motion information, which provides an important reference for UAV recognition. The low flight altitude and small radar cross-section (RCS) of UAVs make the cancellation of strong ground clutter become a key problem in extracting the weak micro-Doppler signals. In this paper, a clutter suppression method based on an orthogonal matching pursuit (omp) algorithm is proposed, which is used to process echo signals obtained by a linear frequency modulated continuous wave (LFMCW) radar. The focus of this method is on the idea of sparse representation, which establishes a complete set of environmental clutter dictionaries to effectively suppress clutter in the received echo signals of a hovering UAV. The processed signals are analyzed in the time-frequency domain. According to the flicker phenomenon of UAV rotor blades and related micro-Doppler characteristics, the feature parameters of unknown UAVs can be estimated. Compared with traditional signal processing methods, the method based on omp algorithm shows advantages in having a low signal-to-noise ratio (-10 dB). Field experiments indicate that this approach can effectively reduce clutter power (-15 dB) and successfully extract micro-Doppler signals for identifying different UAVs.

关键词： radar signal processing identification of UAV omp algorithm clutter suppression micro-Doppler

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Electrical Resistance Tomography Image Reconstruction Based on Modified omp algorithm

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IEEE SENSORS JOURNAL 2019年第14期19卷 5723-5731页

作者： Zhang, Wei Tan, Chao Xu, Yanbin Dong, Feng Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Proc Measurement & Control Tianjin 300072 Peoples R China

Electrical resistance tomography (ERT) is a sensing technique for process monitoring and measurement, the image reconstruction algorithms are required fast and accurate. The omp class algorithm has the property of reconstructing a higher quality signal by fewer iteration steps (shorter elapsed time) and faster convergence speed compared with other iterative algorithms. But the classical omp is not self-adapted and may fall into a local optimal solution. In this paper, a modified orthogonal matching pursuit (Momp) was presented by adding a continuous constraint to prevent local optimal solution and self-adaption process on classical omp algorithm which finds the optimal number of iterations based on the information entropy of measurement to make it suitable for ERT inverse problem. The algorithm was experimentally validated versus other algorithms through a 16-electrode ERT system. Comparing with other algorithms, Momp algorithm has a lower mean square error than non-iterative algorithms and a shorter time cost than iterative algorithms. Dynamic experiments showed that the Momp algorithm is promising for industrial process monitoring.

关键词： Electrical resistance tomography image reconstruction compressed sensing omp algorithm

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Multi-level Off grid DOA estimation of sparse arrays Using omp algorithm

Multi-level Off grid DOA estimation of sparse arrays Using O...

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IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS)

作者： Neela, Pavani Vakkalagadda, Swathi Padidam, Pushyami Puli, Kishore Kumar NIT Andhra Pradesh Dept ECE Tadepalligudem India

ISBN: (纸本)9781538695494

Direction Of Arrival (DOA) estimation plays a major role in the operation of smart antennas. It has been a research area in array signal processing since decades. Although there are many algorithms to solve this problem, each algorithm has its own advantages and disadvantages. Recently, Compressive Sensing (CS) technique revolutionised the idea of sampling in signal processing. We can have sparse representation of DOA problem using angular grid model and hence CS techniques can be used to solve for DOA's. Using the idea of CS, even one snapshot is sufficient to estimate the angles. Orthogonal Matching Pursuit (omp), one of the algorithm in the class of greedy algorithms is used in this paper for DOA estimation. The simulations using this algorithm for uniform linear array and sparse array shows the performance of the algorithm. Also off grid model is employed to find DOA of sources that are impinging in grid spaces i.e., between grid points.

关键词： DOA estimation Compressive Sensing omp algorithm smart antennas Off grid model

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Research of wind turbine clutter mitigation based on omp algorithm

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JOURNAL OF ENGINEERING-JOE 2019年第19期2019卷 5689-5692页

作者： Cao, Yonggui Fang, Yu Wu, Daoqing Nanjing Res Inst Elect Technol Nanjing 210012 Jiangsu Peoples R China

With the rapid development of wind power generation, the number of installed wind turbine increases rapidly. Research shows that radar echoes from wind turbines may have the potential to distract and confuse the target signal by creating false detection. To solve this problem, this study proposes a method based on orthogonal matching pursuit (omp) algorithm for clutter mitigation. The algorithm first establishes an echo dictionary matrix and filters out clutter through loop operations. Experiments show that the method effectively filters the clutter of the wind turbine.

关键词： wind turbines radar clutter iterative methods time-frequency analysis radar detection wind power plants matrix algebra radar echoes orthogonal matching pursuit algorithm echo dictionary matrix wind turbine clutter mitigation omp algorithm wind power generation false detection loop operations

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Compressive Sensing Based Off-Grid DOA Estimation Using omp algorithm 6

Compressive Sensing Based Off-Grid DOA Estimation Using OMP ...

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6th International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Ganguly, Saurav Ghosh, Ishita Ranjan, Ratnesh Ghosh, Jayanta Kumar, Puli Kishore Mukhopadhyay, Mainak Natl Inst Technol Dept ECE Patna Bihar India Deloitte India Off US IoT Serv Bengaluru India Natl Inst Technol Dept ECE Tadepalligudem Andhra Pradesh India Birla Inst Technol Dept ECE Deoghar Campus Mesra India

ISBN: (纸本)9781728113807

In this paper we present a method of Direction of Arrival (DOA) estimation using a sparse array based on compressive sensing. The sources are assumed to be at off -grid location with respect to the receiver array. NV.: show that the off -grid DOA of the sources can be estimated almost accurately by using the Orthogonal Matching Pursuit (omp) algorithm for reconstruction from the sparse samples.

关键词： Off-grid DOA estimation compressive sensing sparse array omp algorithm

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Integrating Subspace Correlations and Local Similarity: A Novel Approach to Spectral Clustering 7

Integrating Subspace Correlations and Local Similarity: A No...

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7th International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Guan, Rui Long, Zhiguo Yang, Wu Meng, Hua Southwest Jiaotong Univ Sch Comp & Artificial Intelligence Chengdu 611756 Peoples R China Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 611756 Peoples R China Southwest Jiaotong Univ Sch Math Chengdu 611756 Peoples R China

ISBN: (纸本)9798350385113;9798350385106

Spectral clustering is effective for local similarity detection of low-dimensional data, adept at handling non-convex distributions and complex structures. Yet, it struggles with high-dimensional data due to the "curse of dimensionality." In contrast, subspace clustering excels in high-dimensional spaces by identifying subspace structures but falls short with non-convex low-dimensional data. This paper presents a novel adaptive clustering algorithm that combines the advantages of spectral and subspace clustering, overcoming their individual limitations across different data dimensions. By dynamically adjusting its strategy according to data dimensionality-utilizing spectral clustering for low-dimensional data to capture local features and subspace clustering for high-dimensional data to exploit subspace relationships-the algorithm offers flexible and effective clustering for diverse datasets. Our extensive experiments on both synthetic and real-world datasets demonstrate significant improvements in clustering performance, showcasing the capability of the algorithm to adapt and excel across varying dimensions.

关键词： spectral clustering omp algorithm similarity matrix similarity fusion

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3D Compressed Spectrum Mapping With Sampling Locations Optimization in Spectrum-Heterogeneous Environment

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第1期21卷 326-338页

作者： Shen, Feng Wang, Zheng Ding, Guoru Li, Kezhi Wu, Qihui Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum Minist Ind & Informat Technol Nanjing 211106 Peoples R China Southeast Univ Sch Informat Sci & Engn Nanjing 210096 Peoples R China Nanjing Univ Aeronaut & Astronaut NUAA Coll Elect & Informat Engn Nanjing 211106 Peoples R China Army Engn Univ Coll Commun Engn Nanjing 210007 Peoples R China UCL Inst Hlth Informat London NW1 2DA England

Spectrum mapping has emerged as an important problem in wireless communications, which generates a spectrum map for the spectrum resource analysis and management. Given the constrained transceiver volume and the limited energy consumption, how to effectively reconstruct the spectrum situation by the limited sampling data is a pressing challenge for spectrum mapping. In this paper, by exploiting the sparse nature of spectrum situation, we firstly attempt to solve the three-dimensional (3D) compressed spectrum mapping problem in the way of compressed sensing. Then, we develop a quadrature and right-triangular (QR) pivoting based measurement matrix optimization algorithm. By iteratively selecting new dominant sampling locations, it promotes the recovery accuracy compared to random measurement. After that, we propose a 3D spatial subspace based orthogonal matching pursuit (omp) algorithm to recover spectrum situation for 3D compressed spectrum mapping. Finally, simulations are presented to show the comparisons in terms of localization, source signal strength recovery, recovery success rate and situation recovery. Results show our proposed 3D spectrum mapping scheme not only effectively reduces the sampling number, but also achieves a high level of spectrum mapping accuracy.

关键词： Three-dimensional displays Matching pursuit algorithms Compressed sensing Wireless communication Solid modeling Radio frequency Optimization Spectrum mapping compressed sensing spectrum-heterogeneity omp algorithm

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Wideband Spectrum Sensing Using Modulated Wideband Converter and Data Reduction Invariant algorithms

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SENSORS 2023年第4期23卷 2263-2263页

作者： Burel, Gilles Radoi, Emanuel Gautier, Roland Le Jeune, Denis Univ Brest CNRS Lab STICC CS 93837 6 Ave Gorgeu F-29238 Brest 3 France ENSTA Bretagne CNRS Lab STICC 2 Rue Francois Verny F-29806 Brest 9 France

Wideband spectrum sensing is a challenging problem in the framework of cognitive radio and spectrum surveillance, mainly because of the high sampling rates required by standard approaches. In this paper, a compressed sensing approach was considered to solve this problem, relying on a sub-Nyquist or Xsampling scheme, known as a modulated wideband converter. First, the data reduction at its output is performed in order to enable a highly effective processing scheme for spectrum reconstruction. The impact of this data transformation on the behavior of the most popular sparse reconstruction algorithms is then analyzed. A new mathematical approach is proposed to demonstrate that greedy reconstruction algorithms, such as Orthogonal Matching Pursuit, are invariant with respect to the proposed data reduction. Relying on the same formalism, a data reduction invariant version of the LASSO (least absolute shrinkage and selection operator) reconstruction algorithm was also introduced. It is finally demonstrated that the proposed algorithm provides good reconstruction results in a wideband spectrum sensing scenario, using both synthetic and measured data.

关键词： Xsampling modulated wideband converter compressed sensing data reduction omp algorithm LASSO algorithm wideband spectrum sensing

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Real Micro-Doppler Parameters Extraction of Spinning Targets Based on Rotating Interference Antenna

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REMOTE SENSING 2022年第21期14卷 5300-5300页

作者： Wang, Zhihao Chen, Yijun Yuan, Hang Luo, Ying Zhang, Qun Air Force Engn Univ Informat & Nav Coll Xian 710077 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Engn Univ PAP Coll Informat Engn Xian 710086 Peoples R China

Micro-Doppler is a unique characteristic of targets with micro-motions, which can provide significant information for target classification and recognition. However, the monostatic radar has the shortcoming of only obtaining the radial micro-motion characteristics. Although the vortex-electromagnetic-wave-based radar has the potential to obtain real micro-motion parameters, it has a high dependence on the mode number and purity of the orbital angular momentum, which greatly restricts its application in the micro-motion parameter extraction. To overcome the above problems, a new radar configuration based on the rotating interference antenna is proposed in this paper. Through the interference processing of the micro-Doppler curves of the rotating and fixed antenna, the curves containing the real micro-motion information of the target can be obtained. Then the real micro-motion characteristics of the spinning target can be reconstructed by the orthogonal matching pursuit algorithm. The effectiveness and robustness of the proposed method are validated by simulations.

关键词： rotating interference antenna spinning targets micro-Doppler parameters extraction omp algorithm

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Uplink Analysis of Cell-Free Massive MIMO System Combined with Index Modulation 12

Uplink Analysis of Cell-Free Massive MIMO System Combined wi...

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12th International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Huang, Mouhua Xu, Kui Zhang, Dongmei Army Engn Univ PLA Nanjing 210007 Peoples R China

ISBN: (纸本)9781728172361

In this paper, the uplink transmission scheme combining spatial index modulation with cell-free massive multi-input multi-output (MIMO) system is studied. The access point (AP) and users in the cell-free network have multiple antennas, which inherits the advantages of macro diversity and interference cancellation of massive distributed MIMO with large-scale AP, and improve the system reliability. In the user transmitter, multiple active spatial modulation (MA-SM) can be directly used to process the transmitted information. The index information can be mapped into the active antenna by using the combinatorial method, while the orthogonal matching pursuit (omp) algorithm is used for demodulation and decoding in the central processing unit (CPU). Simulation results show that index modulation has better decoding performance on the basis of correct estimation of channel information, and the more antennas the user has, the better index modulation performance will be.

关键词： omp algorithm Cell-Free MIMO Index Modulation

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