Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characterist...Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.展开更多
In this paper,we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector.Through iteration,the proposed algorithm automatically selects the echo si...In this paper,we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector.Through iteration,the proposed algorithm automatically selects the echo signal of isolated strong-scattering points from the receiving echo signal data to accurately estimate the actual optimal monopulse response curve(MRC) of the same distance range,and we applied optimal MRC to realize the azimuth self-focusing in the process of imaging.We use real-time echo data to perform error correction for obtaining the optimal MRC,and the azimuth angulation accuracy may reach the optimum at a certain distance dimension.We experimentally demonstrate the validity,reliability and high performance of the proposed algorithm.The azimuth angulation accuracy may reach up to ten times of the detection beam-width.The simulation experiments have verified the feasibility of this strategy,with the average height measurement error being 7.8%.In the out-field unmanned aerial vehicle(UAV) tests,the height measurement error is less than 25 m,and the whole response time can satisfy the requirements of a missile-borne detector.展开更多
Aiming at a novel missile-borne detector in the optional burst height proximity fuze, a self-adaptive high-resolution forward-looking imaging algorithm (SAHRFL-IA) is presented. The echo data are captured by the missi...Aiming at a novel missile-borne detector in the optional burst height proximity fuze, a self-adaptive high-resolution forward-looking imaging algorithm (SAHRFL-IA) is presented. The echo data are captured by the missile-borne detector in the target regions;thereby the azimuth angulation accuracy at the same distance dimension is improved dynamically. Thus, azimuth information of the targets in the detection area may be obtained accurately. The proposed imaging algorithm breaks through the conventional misconception of merely using azimuth discrimination curves under ideal conditions during monopulse angulation. The real-time echo data from the target region are used to perform error correction for this discrimination curve, and finally the accuracy of the azimuth angulation may reach the optimum at the same distance dimension. A series of experiments demonstrate the validity, reliability and high performance of the proposed imaging algorithm. Azimuth angulation accuracy may reach ten times that of the detection beam width. Meanwhile, the running time of this algorithm satisfies the requirements of missile-borne platforms.展开更多
Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high comp...Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.展开更多
This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian mod...This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.展开更多
Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The differ...Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The difference between two schemes is the pattern of selecting pulses, which depends on the demand for the velocity information. The system, a type of frequency diverse array (FDA), takes full advantage of the phase-coded orthogonal frequency division multiplexing (OFDM) signal. Furthermore, the complete discrete form of the phase-coded OFDM echoes is utilized to derive the HRRP processing. The velocity estimation in the second scheme aims to eliminate velocity ambiguity, and high velocity can be retrieved exactly. Meanwhile, the imaging method is investigated with random frequency coding applied to an array. The desired performance of resolving velocity ambiguity and suppressing noise is shown by means of comparisons with previous work. The advantages in the radar imaging and the significance of the work are concluded in the end.展开更多
This paper considers the problem of sea clutter sup-pression.We propose the cuttable encoder-decoder-augmenta-tion network(CEDAN)to improve clutter suppression perfor-mance by enriching the contrast information betwee...This paper considers the problem of sea clutter sup-pression.We propose the cuttable encoder-decoder-augmenta-tion network(CEDAN)to improve clutter suppression perfor-mance by enriching the contrast information between the target and clutter.Specifically,the plug-and-play residual U-block(ResUblock)is proposed to augment the feature representation ability of the clutter suppression model.The CEDAN first extracts and fuses the multi-scale features using the encoder and the decoder composed of the ResUblocks.Then,the fused features are processed by the contrast information augmenta-tion module(CIAM)to enhance the diversity of target and clutter,resulting in encouraging sea clutter suppression results.In addi-tion,we propose the result-consistency loss to further improve the suppression performance.The result-consistency loss enables CEDAN to cut some blocks of decoder and CIAM to reduce the inference time without significantly degrading the suppression performance.Experimental results on measured and simulated data show that the CEDAN outperforms state-of-the-art sea clutter suppression methods in sea clutter suppres-sion performance and computation efficiency.展开更多
针对高频地波雷达(High frequency surface wave radar,HFSWR)在探测中产生的回波数据,传统的人工识别和分类方法存在工作量大、效率低和主观性强等问题,本研究在分析一阶海杂波、电离层杂波和射频干扰的回波数据特性的基础上,创新性地...针对高频地波雷达(High frequency surface wave radar,HFSWR)在探测中产生的回波数据,传统的人工识别和分类方法存在工作量大、效率低和主观性强等问题,本研究在分析一阶海杂波、电离层杂波和射频干扰的回波数据特性的基础上,创新性地提出了基于YOLOv5识别模型的HFSWR杂波和干扰识别分类方法。该方法旨在帮助研究人员在海量实验数据中快速筛选出符合其科学研究需求的数据集,从而提高研究效率和数据准确性。在具体实施过程中,通过采用批量实测距离-多普勒(Range-Doppler,RD)谱数据对所提出模型进行训练和分析,使该方法能够在频域范围内对杂波和干扰进行有效识别。本研究以该识别分类算法为核心,进一步基于Python语言设计了一款地波雷达智能杂波和干扰识别分类软件。经过严格的批量实测数据测试验证,该软件能够满足设计需求,具有良好的可靠性,极大地提高了研究人员筛选有效实测数据的工作效率,为科学研究工作提供了有力的技术支撑。展开更多
文摘Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.
基金The name of the project that funded this article is 13th Five-Year Plan"equipment pre-research project,the number of this project is 30107030803。
文摘In this paper,we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector.Through iteration,the proposed algorithm automatically selects the echo signal of isolated strong-scattering points from the receiving echo signal data to accurately estimate the actual optimal monopulse response curve(MRC) of the same distance range,and we applied optimal MRC to realize the azimuth self-focusing in the process of imaging.We use real-time echo data to perform error correction for obtaining the optimal MRC,and the azimuth angulation accuracy may reach the optimum at a certain distance dimension.We experimentally demonstrate the validity,reliability and high performance of the proposed algorithm.The azimuth angulation accuracy may reach up to ten times of the detection beam-width.The simulation experiments have verified the feasibility of this strategy,with the average height measurement error being 7.8%.In the out-field unmanned aerial vehicle(UAV) tests,the height measurement error is less than 25 m,and the whole response time can satisfy the requirements of a missile-borne detector.
基金supported by the Key Army Pre-research Projects of China(30107030803)
文摘Aiming at a novel missile-borne detector in the optional burst height proximity fuze, a self-adaptive high-resolution forward-looking imaging algorithm (SAHRFL-IA) is presented. The echo data are captured by the missile-borne detector in the target regions;thereby the azimuth angulation accuracy at the same distance dimension is improved dynamically. Thus, azimuth information of the targets in the detection area may be obtained accurately. The proposed imaging algorithm breaks through the conventional misconception of merely using azimuth discrimination curves under ideal conditions during monopulse angulation. The real-time echo data from the target region are used to perform error correction for this discrimination curve, and finally the accuracy of the azimuth angulation may reach the optimum at the same distance dimension. A series of experiments demonstrate the validity, reliability and high performance of the proposed imaging algorithm. Azimuth angulation accuracy may reach ten times that of the detection beam width. Meanwhile, the running time of this algorithm satisfies the requirements of missile-borne platforms.
基金supported by the National Natural Science Foundation of China(61671469)
文摘Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.
基金supported by the National Natural Science Foundation of China(62371382,62071346)the Science,Technology&Innovation Project of Xiong’an New Area(2022XAGG0181)the Special Funds for Creative Research(2022C61540)。
文摘This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.
基金supported by the National Natural Science Foundation of China(6107116361071164+8 种基金6147119161501233)the Fundamental Research Funds for the Central Universities(NP2014504)the Aeronautical Science Foundation(20152052026)the Electronic&Information School of Yangtze University Innovation Foundation(2016-DXCX-05)the Funding for Outstanding Doctoral Dissertation in NUAA(BCXJ15-03)the Funding of Jiangsu Innovation Program for Graduate Education(KYLX15 0281)the Fundamental Research Funds for the Central Universitiespartly funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA)
文摘Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The difference between two schemes is the pattern of selecting pulses, which depends on the demand for the velocity information. The system, a type of frequency diverse array (FDA), takes full advantage of the phase-coded orthogonal frequency division multiplexing (OFDM) signal. Furthermore, the complete discrete form of the phase-coded OFDM echoes is utilized to derive the HRRP processing. The velocity estimation in the second scheme aims to eliminate velocity ambiguity, and high velocity can be retrieved exactly. Meanwhile, the imaging method is investigated with random frequency coding applied to an array. The desired performance of resolving velocity ambiguity and suppressing noise is shown by means of comparisons with previous work. The advantages in the radar imaging and the significance of the work are concluded in the end.
基金supported by the National Natural Science Foundation of China(62271126).
文摘This paper considers the problem of sea clutter sup-pression.We propose the cuttable encoder-decoder-augmenta-tion network(CEDAN)to improve clutter suppression perfor-mance by enriching the contrast information between the target and clutter.Specifically,the plug-and-play residual U-block(ResUblock)is proposed to augment the feature representation ability of the clutter suppression model.The CEDAN first extracts and fuses the multi-scale features using the encoder and the decoder composed of the ResUblocks.Then,the fused features are processed by the contrast information augmenta-tion module(CIAM)to enhance the diversity of target and clutter,resulting in encouraging sea clutter suppression results.In addi-tion,we propose the result-consistency loss to further improve the suppression performance.The result-consistency loss enables CEDAN to cut some blocks of decoder and CIAM to reduce the inference time without significantly degrading the suppression performance.Experimental results on measured and simulated data show that the CEDAN outperforms state-of-the-art sea clutter suppression methods in sea clutter suppres-sion performance and computation efficiency.
文摘针对高频地波雷达(High frequency surface wave radar,HFSWR)在探测中产生的回波数据,传统的人工识别和分类方法存在工作量大、效率低和主观性强等问题,本研究在分析一阶海杂波、电离层杂波和射频干扰的回波数据特性的基础上,创新性地提出了基于YOLOv5识别模型的HFSWR杂波和干扰识别分类方法。该方法旨在帮助研究人员在海量实验数据中快速筛选出符合其科学研究需求的数据集,从而提高研究效率和数据准确性。在具体实施过程中,通过采用批量实测距离-多普勒(Range-Doppler,RD)谱数据对所提出模型进行训练和分析,使该方法能够在频域范围内对杂波和干扰进行有效识别。本研究以该识别分类算法为核心,进一步基于Python语言设计了一款地波雷达智能杂波和干扰识别分类软件。经过严格的批量实测数据测试验证,该软件能够满足设计需求,具有良好的可靠性,极大地提高了研究人员筛选有效实测数据的工作效率,为科学研究工作提供了有力的技术支撑。
