A multichannel noncoherent integration detection method based on high range resolution profile was presented in this paper.According to the property of the moment-generating function,the distribution characteristics o...A multichannel noncoherent integration detection method based on high range resolution profile was presented in this paper.According to the property of the moment-generating function,the distribution characteristics of the noncoherent integrated signals with or without target presence were derived under the circumstance with noncorrelated Gaussian distribution noises.The loss of noncoherent integration was due to improper selection of integration range of cell numbers.A multichannel noncoherent integration detection scheme where the integration number in each channel varies was proposed to solve this problem.The quality of this method for detection of various targets was evaluated.A comparison of fixed integration range cell number detection and multichannel integration detection for a high range resolution profile was presented.Simulation results indicated that the principle of the method was correct and performed well for unknown physical dimension targets.The method required little prior knowledge about target and was convenient for practical implementation.展开更多
In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which increases the computational load.Balancing the computational load and the range resolution is challenging.Thi...In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which increases the computational load.Balancing the computational load and the range resolution is challenging.This paper presents a method to trade off the range resolution and the computational load by experimentally determining the optimal sampling frequency through an analysis of multiple sets of GPS satellite data at different sampling frequencies.The test data are used to construct a range resolution-sampling frequency trade-off model using least-squares estimation.The theoretical analysis shows that the experimental data are the best fit using smoothing and nthorder derivative splines.Using field GPS C/A code signal-based GPS radar,the trade-off between the optimal sampling frequency is determined to be in the 20461.25–24553.5 kHz range,which supports a resolution of 43–48 m.Compared with the conventional method,the CPU time is reduced by approximately 50%.展开更多
The approach to estimate the length of extended targets by using the bistatic high resolution range profile( H RRP) is analyzed in this paper. The relationship between the bistatic H RRP and the monostatic H RRP of ex...The approach to estimate the length of extended targets by using the bistatic high resolution range profile( H RRP) is analyzed in this paper. The relationship between the bistatic H RRP and the monostatic H RRP of extended targets are investigated. It is demonstrated by simulations that the target length measured by the bistatic H RRP is more meaningful and accurate than that by the monostatic HRRP,though the monostatic H RRP has been well developed and widely used in target recognizing and classification. The estimation results of a cone shaped target are present and compared at the end of the paper. To assure the reliability of the simulation,the bistatic H RRP is obtained through the scattering field data calculated by a fullwave numerical method,FE-BI-MLFMA.展开更多
Template database is the key to radar automation target recognition based on High Resolution Range Profile (HRRP). From the traditional perspective, average HRRP is a valid template for it can represent each HRRP with...Template database is the key to radar automation target recognition based on High Resolution Range Profile (HRRP). From the traditional perspective, average HRRP is a valid template for it can represent each HRRP without scatterer Moving Through Range Cell (MTRC). However, template database based on this assumption is always challenged by measured data. One reason is that speckle happens in the frame without scatterer MTRC. Speckle makes HRRP fluctuate sharply and not match well with the average HRRP. We precisely introduce the formation mechanism of speckle. Then, we make an insight into the principle of matching score. Based on the conclusion, we study the properties of matching score between speckled HRRP and the average HRRP. The theoretical analysis and Monte Carlo experimental results demonstrate that speckle makes HRRP not to match well with the average HRRP according to the energy ratio of speckled scatterers. On the assumption of ideal scattering centre model, speckled HRRP has a matching score less than 85% with the average HRRP if speckled scatterers occupy more than 50% energy of the target.展开更多
When range high-resolution radar is applied to target recognition,it is quite possible for the high-resolution range profiles(HRRPs)of group targets in a beam to overlap,which reduces the target recognition performanc...When range high-resolution radar is applied to target recognition,it is quite possible for the high-resolution range profiles(HRRPs)of group targets in a beam to overlap,which reduces the target recognition performance of the radar.In this paper,we propose a group target recognition method based on a weighted mean shift(weighted-MS)clustering method.During the training phase,subtarget features are extracted based on the template database,which is established through simulation or data acquisition,and the features are fed to the support vector machine(SVM)classifier to obtain the classifier parameters.In the test phase,the weighted-MS algorithm is exploited to extract the HRRP of each subtarget.Then,the features of the subtarget HRRP are extracted and used as input in the SVM classifier to be recognized.Compared to the traditional group target recognition method,the proposed method has the advantages of requiring only a small amount of computation,setting parameters automatically,and having no requirement for target motion.The experimental results based on the measured data show that the method proposed in this paper has better recognition performance and is more robust against noise than other recognition methods.展开更多
A high resolution range profile(HRRP) is a summation vector of the sub-echoes of the target scattering points acquired by a wide-band radar.Generally, HRRPs obtained in a noncooperative complex electromagnetic environ...A high resolution range profile(HRRP) is a summation vector of the sub-echoes of the target scattering points acquired by a wide-band radar.Generally, HRRPs obtained in a noncooperative complex electromagnetic environment are contaminated by strong noise.Effective pre-processing of the HRRP data can greatly improve the accuracy of target recognition.In this paper, a denoising and reconstruction method for HRRP is proposed based on a Modified Sparse Auto-Encoder, which is a representative non-linear model.To better reconstruct the HRRP, a sparse constraint is added to the proposed model and the sparse coefficient is calculated based on the intrinsic dimension of HRRP.The denoising of the HRRP is performed by adding random noise to the input HRRP data during the training process and fine-tuning the weight matrix through singular-value decomposition.The results of simulations showed that the proposed method can both reconstruct the signal with fidelity and suppress noise effectively, significantly outperforming other methods, especially in low Signal-to-Noise Ratio conditions.展开更多
基金Supported by the Advanced Research Foundation of General Armament Department(51307020101)
文摘A multichannel noncoherent integration detection method based on high range resolution profile was presented in this paper.According to the property of the moment-generating function,the distribution characteristics of the noncoherent integrated signals with or without target presence were derived under the circumstance with noncorrelated Gaussian distribution noises.The loss of noncoherent integration was due to improper selection of integration range of cell numbers.A multichannel noncoherent integration detection scheme where the integration number in each channel varies was proposed to solve this problem.The quality of this method for detection of various targets was evaluated.A comparison of fixed integration range cell number detection and multichannel integration detection for a high range resolution profile was presented.Simulation results indicated that the principle of the method was correct and performed well for unknown physical dimension targets.The method required little prior knowledge about target and was convenient for practical implementation.
基金supported by the National Natural Science Foundation of China(42001297)the Research Foundation of Education Department of Hunan Province(19B061)the National Natural Science Foundation of Hunan Province(2021JJ40631)。
文摘In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which increases the computational load.Balancing the computational load and the range resolution is challenging.This paper presents a method to trade off the range resolution and the computational load by experimentally determining the optimal sampling frequency through an analysis of multiple sets of GPS satellite data at different sampling frequencies.The test data are used to construct a range resolution-sampling frequency trade-off model using least-squares estimation.The theoretical analysis shows that the experimental data are the best fit using smoothing and nthorder derivative splines.Using field GPS C/A code signal-based GPS radar,the trade-off between the optimal sampling frequency is determined to be in the 20461.25–24553.5 kHz range,which supports a resolution of 43–48 m.Compared with the conventional method,the CPU time is reduced by approximately 50%.
基金Supported by the National Natural Science Fundation of China(61001192)
文摘The approach to estimate the length of extended targets by using the bistatic high resolution range profile( H RRP) is analyzed in this paper. The relationship between the bistatic H RRP and the monostatic H RRP of extended targets are investigated. It is demonstrated by simulations that the target length measured by the bistatic H RRP is more meaningful and accurate than that by the monostatic HRRP,though the monostatic H RRP has been well developed and widely used in target recognizing and classification. The estimation results of a cone shaped target are present and compared at the end of the paper. To assure the reliability of the simulation,the bistatic H RRP is obtained through the scattering field data calculated by a fullwave numerical method,FE-BI-MLFMA.
文摘Template database is the key to radar automation target recognition based on High Resolution Range Profile (HRRP). From the traditional perspective, average HRRP is a valid template for it can represent each HRRP without scatterer Moving Through Range Cell (MTRC). However, template database based on this assumption is always challenged by measured data. One reason is that speckle happens in the frame without scatterer MTRC. Speckle makes HRRP fluctuate sharply and not match well with the average HRRP. We precisely introduce the formation mechanism of speckle. Then, we make an insight into the principle of matching score. Based on the conclusion, we study the properties of matching score between speckled HRRP and the average HRRP. The theoretical analysis and Monte Carlo experimental results demonstrate that speckle makes HRRP not to match well with the average HRRP according to the energy ratio of speckled scatterers. On the assumption of ideal scattering centre model, speckled HRRP has a matching score less than 85% with the average HRRP if speckled scatterers occupy more than 50% energy of the target.
文摘When range high-resolution radar is applied to target recognition,it is quite possible for the high-resolution range profiles(HRRPs)of group targets in a beam to overlap,which reduces the target recognition performance of the radar.In this paper,we propose a group target recognition method based on a weighted mean shift(weighted-MS)clustering method.During the training phase,subtarget features are extracted based on the template database,which is established through simulation or data acquisition,and the features are fed to the support vector machine(SVM)classifier to obtain the classifier parameters.In the test phase,the weighted-MS algorithm is exploited to extract the HRRP of each subtarget.Then,the features of the subtarget HRRP are extracted and used as input in the SVM classifier to be recognized.Compared to the traditional group target recognition method,the proposed method has the advantages of requiring only a small amount of computation,setting parameters automatically,and having no requirement for target motion.The experimental results based on the measured data show that the method proposed in this paper has better recognition performance and is more robust against noise than other recognition methods.
基金co-supported by the National Natural Science Foundation of China(Nos.61671463,61471379,61790551 and 61102166)。
文摘A high resolution range profile(HRRP) is a summation vector of the sub-echoes of the target scattering points acquired by a wide-band radar.Generally, HRRPs obtained in a noncooperative complex electromagnetic environment are contaminated by strong noise.Effective pre-processing of the HRRP data can greatly improve the accuracy of target recognition.In this paper, a denoising and reconstruction method for HRRP is proposed based on a Modified Sparse Auto-Encoder, which is a representative non-linear model.To better reconstruct the HRRP, a sparse constraint is added to the proposed model and the sparse coefficient is calculated based on the intrinsic dimension of HRRP.The denoising of the HRRP is performed by adding random noise to the input HRRP data during the training process and fine-tuning the weight matrix through singular-value decomposition.The results of simulations showed that the proposed method can both reconstruct the signal with fidelity and suppress noise effectively, significantly outperforming other methods, especially in low Signal-to-Noise Ratio conditions.
