In near-space fast-speed synthetic aperture radar (SAR), the azimuth multichannel technology is usually required to achieve high resolution wide swath (HRWS) imaging. Compared with traditional linear array SAR (LA-SAR), arc array SAR (AA-SAR) is with attractive omnidirectional and real-time dynamic imaging capacities. In the paper, the azimuth multichannel signal model of LA-SAR and AA-SAR are both established and compared, compared with the echo model of linear array SAR, the echo model of arc array SAR has an additional phase, which leads to the imbalance of multichannel. Directly using the linear array azimuth multi-channel reconstruction method, the imaging results will appear false targets. Finally, the inference is verified by point target simulation.
KEYWORDS: Data acquisition, Field programmable gate arrays, Extremely high frequency, Design and modelling, Data processing, Radar signal processing, Radar, Computing systems, Digital signal processing, Data transmission
For the current millimeter wave radar imaging data volume than the mud level meter, rain gauge and other single-point monitoring means of data volume tens of times or hundreds of times geometrically increasing and other challenges, in order to meet the data acquisition computing needs, designed based on FPGA ground disaster system data acquisition computing design of colleges and universities. First of all, we analyzed the requirements of data acquisition of ground disaster system, designed the overall architecture of the system based on FPGA, developed XC7K325T as the main control chip, ADC analog-to-digital conversion and other related modules in one, and then conducted experimental verification of the data acquisition and operation system of ground disaster system, which proved that the system has good acquisition and processing performance, and effectively overcame the problems of large amount of data acquisition of ground disaster system and inaccurate acquisition and operation processing. The system can effectively overcome the problems of large volume of data collection and inaccuracy of data collection and processing, and is conducive to the subsequent data processing of the ground disaster system.
Ground-based radar has been widely used for deformation monitoring and early warning of geological hazard potential areas. However, during long-term monitoring, ground-based radar images are vulnerable to human and environmental factors leading to severe decoherence. The study of ground-based radar image change detection can provide reference information for its long-term monitoring. Based on this, an unsupervised change detection method based on convolutional neural network (CNN) for ground-based radar images is proposed in this paper. First, the interference principle to extract change information is used for the first time for the change detection task, aiming to improve the accuracy of the initial extraction of change regions. Secondly, the fuzzy c-means clustering algorithm is used to obtain the pseudo-label matrix with categories, and the appropriate neighborhood image blocks with pseudo-labels are selected as training samples to train CNN. Finally, the change detection results of ground-based radar images are obtained using the trained CNN. Experiments were conducted using actual measurement data from ground-based radar in a monitoring task in a mining area in China and compared with other methods to verify the effectiveness of this paper's method and more accurate detection results.
Rapid extraction of ship target information in Synthetic Aperture Radar (SAR) images plays an important role in sea surface monitoring and military prevention. However, the existing detection algorithms have disadvantages such as large model volume and slow detection speed, which are not suitable for the requirements of future star-earth integrated target detection. To solve these problems, this article proposes a SAR ship target detection method based on the improved Nanodet algorithm. To solve the problem of multi-level feature map fusion, the Ghost-pan module is added to the network to enlarge the receptive field and better fuse multi-scale features. At the same time, Resnet18 is used instead of the original backbone network, and depth-wise separable convolution is used instead of ordinary convolution to reduce the model parameter volume and improve detection efficiency. Conducted ablation experiments on the SAR dataset, and the results show that the proposed method achieves better accuracy and faster detection speed.
Waveform optimization technology based on phase encoding has become a key technology to improve the ability of radar to detect small targets. Designing different phase encoding models for different application scenarios and platforms can effectively improve the performance of radar in complex environments such as clutter and interference. Therefore, it’s very important to design an optimization algorithm with high orthogonality and fast convergence. This paper proposes an improved dynamic genetic algorithm to solve the optimization problem of Multi-Input Multi-Output radar phase encoding signal set. By improving the optimization model of the genetic algorithm, the diversity of the population is quantified to prevent the algorithm from converging prematurely. The improved dynamic genetic algorithm reduces the genetic probability of inferior individuals in the selection operation, then proposes to update the crossover probability in the crossover operation, and finally designs the mutation probability for individual gene points in the mutation operation, which solves the key problem of poor diversity in existing algorithms question. The simulation results show that the improved dynamic genetic algorithm improves the population diversity, optimizes the convergence speed of the algorithm, and the optimized phase encoding set has good performance, and the result is better than the existing improved genetic algorithm.
Addressing the inefficiencies of conventional stripmap Synthetic Aperture Radar (SAR) imaging in scenarios where the target area does not align with the satellite ground track, this paper introduces a novel approach, the distance scanning off-axis stripmap imaging mode. This innovative mode dynamically adjusts the slant angle, Pulse Repetition Frequency (PRF), and start of sampling to adapt to complex imaging scenarios, thereby enhancing imaging efficiency and reducing imaging time. The paper also presents a comprehensive SAR system imaging process flowchart, which includes the computation of nadir satellite parameters, analysis of scene inclination angle variation, and definition of the sampling start rule. By employing a block variable PRF, the proposed mode effectively mitigates the issues associated with large range migration in conventional stripmap imaging. The effectiveness of the proposed mode is validated through imaging simulations. The results underscore its potential to enhance the performance of spaceborne SAR systems, particularly in scenarios where the target area does not align with the satellite ground track
The beam scanning range of frequency diversity arc array (FDAA) has all-round advantages. When it is equivalent to a linear array, it exhibits the characteristics of "The middle spacing is large, and the spacing between the two sides is gradually reduced", and there is an inverse density weighting phenomenon, which will lead to a high sidelobe of the FDAA beam. In order to further reduce the influence of sidelobe level and inverse density weighting, the amplitude weighting is carried out on the basis of the nonlinear frequency offset of the array element, but the amplitude weighting is realized by the attenuator in each channel, which will lead to the decrease of the antenna gain, which is generally used when the radar receives the signal. For the transmitter of antenna radar, this paper proposes a phase weighting method for nonlinear frequency offset. The effectiveness of this method for sidelobe suppression is proved by simulation.
In the bistatic arc array synthetic aperture radar (AA-BiSAR) with a moving transmitter, the moving transmitter is helpful to improve the flexibility of the imaging system and expand the imaging scene, which has important significance in the field of helicopter assisted landing, emergency rescue and so on. The motion state of the transmitter is closely related to the bistatic arc array SAR echo model and imaging quality. This article establishes the echo signal model under accelerated motion, analyzes the impact of acceleration on echo phase and imaging quality, studies the effect of different accelerations on the approximate expansion phase error of slant range, and provides relevant analysis results through point target simulation experiments. The analysis results have a certain guiding significance for the follow-up moving transmitter bistatic arc array SAR high-precision and accurate imaging and motion error compensation.
The spaceborne squint sliding spotlight mode provides the capacity to observe the Earth in high resolution with different angles. However, with the increased squint angle, the imaged swath is obviously reduced due to the large range cell migration. To extend the reduced swath, a new spaceborne wide swath sliding spotlight mode with a high squint angle is proposed in this paper. Besides azimuth beam steering to improve the azimuth resolution, antenna beam is also steered in elevation to improve the swath width. The imaging principle of the proposed imaging mode is described in detail, while its corresponding flowcharts of SAR system design and imaging processing are given. Furthermore, the beam steering law of the designed system example with azimuth resolution of 0.5m and swath width of 20km is given, while the imaging result of the designed scene with three targets is given. Both simulation results validate the proposed imaging mode in the high squint case.
Synthetic aperture radar (SAR) system and communication work in the same frequency band, SAR signal will be interfered by communication signal. In this paper, a method based on the combination of intermittent Interrupted SAR and communication is proposed to realize the simultaneous work of radar and communication without affecting each other, so as to realize the integration of radar communication. By analyzing the time domain characteristics and frequency domain characteristics of communication signals, the communication signal is a narrow-band signal in frequency domain, part of the bandwidth of the SAR working frequency band is given up for communication. At this time, the SAR signal is interrupted. The interrupted part of the SAR signal is recovered by linear prediction extrapolation to obtain a complete SAR signal, which solves the interference problem of the SAR system from communication and realizes integration. The effectiveness of this method is proved by SAR point target experiments.
The frequency diversity array (FDA) is capable of producing a range-angle dependent "S" beampattern, unlike conventional phased arrays that only provide directional beams in the angular domain, but it can only scan in a fixed direction, while frequency diversity arc array (FDAA) has a beam scan-ning capability within a 360 degrees range, which can realize all-round monitoring of the target position and provide a more flexible method for radar communication. In this letter, a dot-shaped beampattern optimization method for FDAA is proposed, which uses amplitude weighting and symmetric non-uniform frequency offset to achieve flexible beam scanning
Mining coal mines can cause large scale and extensive surface subsidence in mining areas. It not only affects the economic development of the mine, but also poses a threat to the surrounding environment and the safety of people's lives. Therefore, it is very important to carry out long time surface monitoring in mining area. For D-InSAR (Differential Interferometric Synthetic Aperture Radar) technology is vulnerable to the phenomenon of unstable monitoring results caused by temporal and spatial decoherence and atmospheric delays, this study uses the StaMPS (Stanford Method for Persistent Scatterers) technology for time-series subsidence monitoring. 22 Sentinel-1A images from June 15, 2019 to December 6, 2020 were used to monitor the subsidence of Zhangshuanglou Coal Mine. The results show that: During the monitoring period, there are three obvious subsidence funnels in Zhangshuanglou Coal Mine. The study area is sinking almost all the time with only a brief rebound. The maximum displacement velocity reached -63.9 mm/yr and maximum cumulative displacement value reached -95.8 mm. Moreover, the subsidence value and velocity are almost inversely proportional to the distance to the center of the funnel. This proves that StaMPS technology and Sentinel-1A data can be used to monitor surface subsidence in mining areas and provide a basis for the study of the subsidence pattern and causes of the target area.
Aiming at the problem that the traditional viaduct deformation monitoring has high accuracy but long monitoring period and consumes a lot of manpower and material resources, it is difficult to extract the severe deformation area of viaduct in time. In this paper, based on the small baseline set interferometric synthetic aperture radar (SBAS-InSAR) technology, the deformation information of viaducts and surrounding areas is retrieved, and the severe deformation areas of urban viaducts and surrounding areas are extracted. Taking three viaducts with large traffic flow in Hohhot as the research object, the deformation results of the study area from August 2020 to September 2021 were obtained. The deformation causes are analyzed combined with the inversion results. The results show that there are five large deformation areas in the three viaducts, and the main deformation causes include soil erosion or urban waterlogging caused by rainfall, surface construction and rail transit operation. The research shows that this method can accurately extract the severe deformation area of urban viaducts, and provide a reference for analyzing the causes of viaduct deformation.
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