Building layout surround-view imaging technology can obtain the internal information of the buildings, which has been widely used in the field of the anti-terrorism and combat. The problems of amplitude attenuation, wall widening, position offset, and multipath ghosts caused by the echoes in the process of penetrating between the building walls will bring the great inconvenience to the reconstruction of the building layouts. In this paper, a fusion imaging algorithm based on the amplitude compensation and correction for the building layout is proposed. First, after obtaining as many and accurate wall positions and wall lengths as possible through wall detection, the original image is segmented and then traversed through the adaptive thresholds. Besides, combined with the gray-scale linear method, the sub-images are enhanced, the clutter is suppressed, and its position has been corrected. Finally, the images obtained from multiple perspectives are fused to obtain the complete building layout image. Simulation results show that the proposed method can effectively compensate the attenuation, correct the wall position, suppress the multipath ghosts, and then finally obtain the high-quality and high-precision building layout image.
Low frequency ultra-wideband synthetic aperture radar (LF UWB SAR) not only obtains the high-resolution image, but also has the well capability of the foliage penetrating, which is potential of detecting the concealed target under the vegetation. This paper studies the target change detection based on the Edgeworth statistical distribution features in the LF UWB SAR images. First, the Edgeworth expansion is used to estimate the probability density function of the pixel neighborhood, and then the K-L divergence has been used as the standard to evaluate the difference between the probability density functions, to realize the target change detection in the multi-temporal SAR images. Finally, the proposed algorithm is tested based on the LF UWB BSAR data, and then the detection performance is shown and analyzed. The experiment results prove the correctness of the theoretical analysis and the effectiveness of the proposed method.
Low frequency ultra-wideband bistatic synthetic aperture radar (UWB BSAR) not only gets the high-resolution image and increase the scatter information, but also has the well ability of the foliage penetrating, which is potential of detecting the concealed target under the vegetation. This paper studies the performance of the back-projection (BP) algorithm in the time domain and range-Doppler (RD) algorithm in the frequency domain for the low frequency UWB BSAR imaging. First, the basic flow of the BP algorithm and RD algorithm for the low frequency UWB BSAR imaging is deduced. Then, the quality and efficiency of two algorithms for the low frequency UWB BSAR imaging are investigated. Finally, the two algorithms are tested based on the low frequency UWB BSAR simulation data, and the imaging performance of the two algorithms is compared and analyzed. The experiment results prove the correctness of the theoretical analysis and the effectiveness of the proposed methods.
Low frequency ultra-wideband bistatic synthetic aperture radar (UWB BSAR) system is able to penetrate the foliage, get the high-resolution BSAR image, and offer the increased target information. In this paper, the low frequency UWB BSAR electromagnetic scattering characteristic is analyzed. First, the target under the foliage are modeled and discussed. Moreover, the method of moment (MoM) is proposed for the electromagnetic scattering characteristic. Finally, the simulation experiment is conducted for the modeling and analyzing of the electromagnetic scattering characteristic of the targets, which verifies the correctness of the low frequency UWB BSAR electromagnetic scattering characteristic.
Deep learning has been widely used for the ship target detection in the synthetic aperture radar (SAR) images. The existing researches mainly uses the anchor frame-based detection method to generate the candidate frames to extract the specific targets. However, this method requires the additional computing resources to filter out the many repeated candidate frames, which will lead to the poor target positioning accuracy and low detection efficiency. To solve these problems, this paper constructs an anchor-free frame for the ship target detection in the SAR images. An improved lightweight detection method based on the target key point is proposed for the real-time detection of the SAR images, which can achieve the rapid and accurate positioning of the ship targets in the SAR images. The experimental results prove that the proposed method has the better detection performance and stronger generalization capability, which is beneficial to realize the real-time detection of the ship targets.
P-band ultra-wideband synthetic aperture radar (UWB SAR) not only has the characteristics of the high-resolution imaging, but also has the well capability of the foliage penetrating, which is potential of detecting and imaging the concealed target under the vegetation. However, there are a lot of the radio, television and mobile communication signals in the P-band, which are called as the radio frequency interference (RFI) signals. These RFI signals are mixed with target echo signals, which will cause the serious interference in the P-band UWB SAR imaging. The traditional notch method is easy to implement the RFI suppression, so it has been widely used. However, the traditional notch method is to notch each pulse echo individually, which has a high computational complexity. At the same time, the RFI suppression of each pulse echo separately will always lead to a large amount of the residual interference, so the traditional notch method has the poor RFI suppression effect. Based on the traditional notch method, this paper proposes an RFI suppression method based on the two-dimensional frequency domain (2DFD) notch, which can realize one-time processing of all echo pulses so that improve the efficiency of the RFI suppression. Meanwhile, because the bandwidth of the RFI signal is much smaller than that of the SAR echo signal, converting the received SAR echo signal to the 2DFD can further concentrate the energy of the RFI signals, so it has the better RFI suppression effect. The simulation results show that the proposed RFI suppression method based on the 2DFD notch can not only improve the efficiency of the RFI suppression but also have the better effect of the RFI suppression.
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