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A Coupled Error Self-Calibration Method for High-Speed Space target Imaging in Stepped-Frequency Radar Based on Minimum Entropy

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IEEE tRANSACtIONS ON AEROSPACE AND ELECtRONIC SYStEMS 2025年第1期61卷 1090-1103页

作者： Li, Pucheng Li, Linghao Lv, Linhan Dong, Zehua Wang, Zhen Ding, Zegang Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 10081 Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc T Radar Res Lab Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401331 Peoples R China

Stepped-frequency chirp radar achieves range high resolution through wideband synthesis, yet it harbors systemic errors. these errors coupled with the motion errors of high-speed space target, render error calibration more challenging and compromise the quality of imaging. to tackle this problem, this article proposes the coupled error self-calibration method for high-speed space target imaging in stepped-frequency based on minimum entropy. First, a parameterized model of echo signals incorporating complex coupled errors is established. this model not only takes into account the errors introduced by the amplitude-phase response characteristics of the stepped-frequency radar system, but also considers errors arising from the motion of high-speed targets. then, analytical relationships between entropy and errors after range pulse compression of subband data, after 2-D imaging of subband data, and after high-resolution synthesis of all subband images are constructed. this stepwise processing strategy decomposed complex errors into three distinct components. Subsequently, employing an adaptive matrix estimation method to separately estimate and calibrate the three decoupled error components ensures a gradual improvement in imaging quality. Finally, the effectiveness of the proposed method is verified through computer simulation and a real experiment.

关键词： Radar imaging Radar Imaging Chirp Entropy Calibration Wideband Coupling error self-calibration high-speed space target imaging minimum entropy stepped-frequency chirp radar

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Scattering mechanism-guided zero-shot PolSAR target recognition

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ISPRS JOURNAL OF PHOtOGRAMMEtRY AND REMOtE SENSING 2025年 220卷 428-439页

作者： Li, Feng Yang, Xiaojing Zhang, Liang Wang, Yanhua Han, Yuqi Zhang, Xin Li, Yang Beijing Inst Technol Radar Res Inst Beijing 100081 Peoples R China Beijing Inst Technol Zhengzhou Res Inst Zhengzhou 450000 Henan Peoples R China Beijing Key Lab Embedded Real time Informat Proc T Beijing 100081 Peoples R China

In response to the challenges posed by the difficulty in obtaining polarimetric synthetic aperture radar (PolSAR) data for certain specific categories of targets, we present a zero-shot target recognition method for PolSAR images. Based on a generative model, the method leverages the unique characteristics of polarimetric SAR images and incorporates two key modules: the scattering characteristics-guided semantic embedding generation module (SE) and the polarization characteristics-guided distributional correction module (DC). the former ensures the stability of synthetic features for unseen classes by controlling scattering characteristics. At the same time, the latter enhances the quality of synthetic features by utilizing polarimetric features, thereby improving the accuracy of zero-shot recognition. the proposed method is evaluated on the GOtCHA dataset to assess its performance in recognizing unseen classes. the experiment results demonstrate that the proposed method achieves SOtA performance in zero-shot PolSAR target recognition ( e.g., improving the recognition accuracy of unseen categories by nearly 20%). Our codes are available at https://***/chuyihuan/Zeroshot-PolSAR-target-recognition.

关键词： PolSAR target recognition Zero-shot learning Scattering center Distributional correction

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Multisubband-GRFt-Based Space target Imaging Algorithm With Low SNR in Stepped Frequency Carrier LFM Radar

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IEEE SENSORS JOURNAL 2025年第1期25卷 1230-1242页

作者： Li, Pucheng Li, Linghao Dong, Zehua Lv, Linhan Wang, Zhen Wang, Ziwen Ding, Zegang Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 100081 Peoples R China Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 100081 Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc T Beijing 100081 Peoples R China Chongqing Innovat Ctr Beijing Inst Technol Chongqing 401331 Peoples R China

to achieve high-resolution imaging of distant space targets, a stepped frequency carrier linear frequency modulation (SFCLFM) radar can be used for prolonged observation. In such circumstances, the target's motion is intricate, the signal-to-noise ratio (SNR) of the echoes is low, and subband phase errors are present. this complexity renders traditional imaging methods susceptible to failure. therefore, an imaging algorithm of the space target based on multiple subbands' generalized radon Fourier transform (MS-GRFt) is proposed. Initially, the signal echo from the space target in the SFCLFM radar is modeled, incorporating subband phase errors and noise into the model. Subsequently, motion parameter coarse estimation is achieved using the GRFt of individual subband data, compensating for translational components using peak values in the parameter domain. Simultaneously, the parameter range of the actual target motion is also obtained. Next, utilizing parallel GRFt to obtain parameter estimation results for each subband data, detecting partial motion parameters using constant false alarm ratio (CFAR) technology after noncoherent accumulation across multiple subbands. Sharpness is employed as the objective function to estimate subband phase errors, and analytical solutions are then derived. Subsequently, error compensation is applied to the GRFt results of multiple subbands, and wideband synthesis is performed in the parameter domain. Finally, CFAR is employed for parameter detection, and point-wise motion compensation (MOCO) is applied to achieve high-resolution range-instantaneous-Doppler (RID) images of space targets. Computer simulations and real experimental results validate the effectiveness of the proposed algorithm.

关键词： Radar imaging Signal to noise ratio Imaging Radar Spaceborne radar Wideband Signal resolution Sensors Chirp modulation time-frequency analysis Low signal-to-noise ratio (SNR) multiple subbands' generalized radon Fourier transform (MS-GRFt) space target imaging stepped frequency carrier linear frequency modulation (SFCLFM) radar

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Vehicle tracking Using Shape-Dependent Mixture Model With Edge-Concentrated Measurements

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IEEE tRANSACtIONS ON INtELLIGENt tRANSPORtAtION SYStEMS 2025年

作者： Wen, Zheng Lan, Jian Zheng, Le Zeng, tao Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 100081 Peoples R China Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc T Beijing 100081 Peoples R China Xi An Jiao Tong Univ Ctr Informat Engn Sci Res Sch Elect & Informat Engn Xian 710049 Peoples R China

For tracking a rectangular vehicle, real-world automotive radar position measurements are distributed not uniformly over the vehicle extension but typically around the edges of the vehicle, i.e., the distribution of measurements is shape-dependent. to describe this phenomenon, a shape-dependent Gaussian mixture measurement model is presented, with each mixture component being used to describe a sub-rectangle region by introducing a shape scaling factor. the shape scaling factor is also shape-dependent and can characterize the measurement spread across the corresponding edge. In this model, parameters and mixture structure are highly shape-dependent, and the rectangular shape prior information is also incorporated. Based on the proposed model, a variational Bayesian approach is derived, which recursively and efficiently estimates the kinematic, shape, shape scaling factors, and orientation states of a vehicle. Additionally, the Doppler velocity measurement can also be integrated into the variational Bayesian framework by introducing a latent variable. this approach can effectively and adaptively describe the complex measurement distribution. From the simulation and real experimental results, the proposed approach has a great improvement in the tracking performance, and the superior performance of the proposed model is more significant in estimating the centroid position compared with the state-of-the-art approaches.

关键词： Radar tracking Radar Shape Shape measurement Radar measurements Doppler effect Velocity measurement Mathematical models Estimation Doppler radar Extended object tracking vehicle tracking automotive radar Doppler velocity variational Bayesian approach

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Optimal Data Acquisition and Height Retrieval in Repeat-track Geosynchronous SAR Interferometry

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REMOtE SENSING 2015年第10期7卷 13367-13389页

作者： Hu, Cheng Li, Yuanhao Dong, Xichao Long, teng Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

Geosynchronous synthetic aperture radar (GEO SAR) will move in a high orbit of similar to 36,000 km with a long integration time of hundreds of seconds. It is obviously impacted by orbital perturbations and the Earth's rotation, which can give rise to un-parallel repeated tracks and induce a squint-looking angle in the repeat-track SAR interferometry (InSAR). thus, the traditional data acquisition method using in the zero-Doppler centroid (ZDC) configuration to generate the GEO InSAR pair will bring about the obvious rotation-induced decorrelation. Moreover, the conventional height retrieval model with the broadside mode imaging geometry and the approximate expression of the interferometric baseline will induce large height and localization errors in the GEO InSAR processing. In this paper, a novel data acquisition method is firstly presented based on a criterion of optimal minimal rotational-induced decorrelation (OMRD). It can significantly improve the coherence of the InSAR pair. then, considering the localization equations in the squint-looking mode and the accurate expression of the interferometric baseline, a modified GEO InSAR height retrieval model is proposed to mitigate the height and localization errors induced by the conventional model. Finally, computer simulations are carried out for the verification of the proposed methods. In a typical inclined GEO InSAR configuration, the averaged total correlation coefficient increases more than 0.4, and height errors of hundreds of meters and localization errors of more than 10 degrees are removed.

关键词： GEO SAR SAR interferometry data acquisition height retrieval

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Background Ionosphere Effects on Geosynchronous SAR Focusing: theoretical Analysis and Verification Based on the BeiDou Navigation Satellite System (BDS)

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IEEE JOURNAL OF SELECtED tOPICS IN APPLIED EARtH OBSERVAtIONS AND REMOtE SENSING 2016年第3期9卷 1143-1162页

作者： Hu, Cheng tian, Ye Yang, Xiaopeng Zeng, tao Long, teng Dong, Xichao Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

Due to the ultra-long aperture time and large coverage characteristics of geosynchronous synthetic aperture radar (GEO SAR), the ionosphere freezing model in the traditional low earth orbit synthetic aperture radar (LEO SAR) imaging is assumed to fail in the GEO SAR, thus it should take the effects of the temporal-spatial variation (tSV) background ionosphere on the GEO SAR imaging into account. Meanwhile, owing to the curved trajectory effects caused by the ultra-long synthetic aperture time of GEO SAR, and the complex geometric kinematic relations between the GEO SAR satellite and the Earth's rotation, the LEO SAR ionospheric effect analysis method based on the traditional kinematic model will be no longer suited to GEO SAR. Moreover, as there are no GEO SAR satellites operating in orbit, how to obtain the real-time ionospheric tEC values on the signal propagation path of GEO SAR satellite has become a great challenge. In this paper, through the establishment of a curved trajectory GEO SAR signal model for long aperture time under the influence of tSV background ionosphere, it has first derived the two-dimensional (2-D) spectrum of GEO SAR signal in the context of background ionosphere, and probed into the GEO SAR 2-D image shift and image defocusing phenomena caused by the background ionosphere, as well as analyzed and summarized the boundary conditions of relevant effects. Concurrently, this paper proposed an approach to equivalently retrieve tEC values on the GEO SAR propagation path based on the BeiDou Navigation Satellite System (BDS) IGSO satellites and combined with the Klobuchar model, which was utilized to equivalently acquire the GEO SAR ionospheric tEC retrieved data. In addition, the retrieved data were used to perform the GEO SAR imaging simulation in the context of the background ionosphere, and verified the correctness of the proposed analysis method.

关键词： Background ionosphere BeiDou Navigation Satellite System geosynchronous synthetic aperture radar (GEO SAR) imaging

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Experimental Results and Algorithm Analysis of DEM Generation Using Bistatic SAR Interferometry With Stationary Receiver

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IEEE tRANSACtIONS ON GEOSCIENCE AND REMOtE SENSING 2015年第11期53卷 5835-5852页

作者： Zeng, tao Zhu, Mao Hu, Cheng tian, Weiming Long, teng Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

this paper presents the theory, algorithm, and results of a new bistatic interferometry synthetic aperture radar (InSAR) method. It employs the data acquired in an innovative bistatic configuration, which uses the orbital sensors as transmitters of opportunity and the stationary receivers on the ground, to generate a digital elevation model (DEM). In the bistatic spaceborne/stationary InSAR configuration, the interferometric phase only depends on the target-receiver range, which could not be obtained directly from the measured bistatic range. therefore, the conventional transforming relationship between the interferometric phase and the topographic height is no longer practical. In order to solve the problem, we introduce a new conversion relationship between the interferometric phase and the topographic height, which is derived by the model of the ellipsoidal projection in the bistatic configuration. Meanwhile, the error analysis of the new conversion is carried out through a simulation. Both the simulated and measured data are used to test and verify the feasibility of the new bistatic InSAR method. In the spaceborne/stationary InSAR experiment, YaoGan-3 (an L-band spaceborne SAR system launched by China) was selected as the transmitter and two stationary receivers were mounted on the top of a tall building. the generated DEM of high quality shows that the presented method performs very well in the bistatic InSAR data process.

关键词： Bistatic synthetic aperture radar (BiSAR) digital elevation model (DEM) interferometry synthetic aperture radar (InSAR)

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A novel SAR interferometry processing method in high resolution spotlight SAR

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JOURNAL OF ELECtROMAGNEtIC WAVES AND APPLICAtIONS 2015年第13期29卷 1785-1802页

作者： Li, YuanHao Hu, Cheng Long, teng Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

Synthetic Aperture Radar Interferometry (InSAR) can produce accurate Digital Elevation Model (DEM), and a novel spotlight SAR can get higher azimuth resolution than conventional strip-map SAR. Hence, the combination of InSAR and spotlight SAR techniques implies the potential to obtain higher resolution DEMs which will show more tiny terrain variations. However, in spotlight InSAR processing, additional azimuth interferometric fringes and misregistration decorrelation will be induced by conventional co-registration methods which ignore azimuth varied Doppler centroids in interpolations. Meanwhile, because interferometric fringes in regions with high resolution terrain variations can easily be damaged by random phase noise, there will generate more unreliable unwrapped phase areas with conventional phase unwrapping methods. to eliminate residual azimuth fringes, misregistration decorrelation and unreliable unwrapped phase areas, this paper firstly proposes a novel spotlight SAR interferometry processing method based on co-registration related to two-dimensional Doppler centroid estimation and joint phase unwrapping, and it is validated by using terraSAR-X spotlight data. the final generated 4mx4m grid space DEM not only preserves high resolution, but also has low root mean square error and absolute mean error which are less than 3m with respect to the Google earth DEM.

关键词： synthetic aperture radar interferometry (InSAR) Doppler centroid estimation phase unwrapping spotlight SAR

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Satellite Component Detection Based Upon Searchable Multiview Features Mapping

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IEEE GEOSCIENCE AND REMOtE SENSING LEttERS 2024年 21卷 1页

作者： Zhang, Zipeng Wang, Wenzheng Deng, Chenwei Han, Yuqi Beijing Inst Technol Sch Informat & Elect Beijing Key Lab Embedded Real Time Informat Proc T Beijing 100081 Peoples R China

Satellite component detection (SCD) is one of the key technologies for on-orbit service (OOS) in space exploration. Unlike detection tasks on the ground, the single illumination in the space environment often leads to significant shadow occlusion when capturing satellite components from multiple viewing angles, resulting in the loss of component information. Existing component detection methods utilize this information to estimate their high-dimensional feature distributions and lack descriptions of the correlations between multiview features. to address this issue, we proposed an SCD based upon searchable multiview features mapping, which describes the distribution of satellite components by capturing both the discrimination between positive and negative samples and the commonality of intraclass components. Specifically, to enhance the connection of multiview features, orthogonal subspaces for different classes are constructed by the improved cosine distance between multiview features which is performed as a subspace metric to represent the discrimination and is used to cluster the mapped features. Besides, considering inherent errors in the mapping process, a loose constraint of the metric is introduced to search for common features, maintaining the local sparsity of multiview features. In the proposed dataset and the public dataset of satellite components, the proposed method achieved mean average precisions (mAP) of 0.878 and 0.862, respectively, outperforming existing state-of-the-art methods.

关键词： Loose constraint orthogonal subspaces satellite component detection (SCD) searchable multiview features Loose constraint orthogonal subspaces satellite component detection (SCD) searchable multiview features

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Marginal Center Loss for Deep Remote Sensing Image Scene Classification

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IEEE GEOSCIENCE AND REMOtE SENSING LEttERS 2020年第6期17卷 968-972页

作者： Wei, tianyu Wang, Jue Liu, Wenchao Chen, He Shi, Hao Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

Recently, remote sensing image scene classification technology has been widely applied in many applicable industries. As a result, several remote sensing image scene classification frameworks have been proposed;in particular, those based on deep convolutional neural networks have received considerable attention. However, most of these methods have performance limitations when analyzing images with large intraclass variations. to overcome this limitation, this letter presents the marginal center loss with an adaptive margin. the marginal center loss separates hard samples and enhances the contributions of hard samples to minimize the variations in features of the same class. Experimental results on public remote sensing image scene data sets demonstrate the effectiveness of our method. After the model is trained using the marginal center loss, the variations in the features of the same class are reduced. Furthermore, a comparison with state-of-the-art methods proves that our model has competitive performance in the field of remote sensing image scene classification.

关键词： Remote sensing training Adaptation models Convolutional neural networks task analysis Data models Industries Convolutional neural network (CNN) marginal center loss remote sensing image scene classification

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