High Resolution Radar Real-Time Signal and Information Processing

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional(1D) high-resolution radar detection, tracking, recognition, and two-dimensional(2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-time processing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and information processing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and information processing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.

SAR Tomography with Improved Non-Local Means Filtering Based on Adaptive Window

In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.

Modeling and Analysis of the Impacts of Temporal-Spatial Variant Troposphere on Ground-Based SAR Imaging of Asteroids

The near-Earth asteroid collisions could cause catastrophic disasters to humanity and the Earth,so it is crucial to monitor asteroids.Ground-based synthetic aperture radar(SAR)is an observation technique for high resolution imaging of asteroids.The ground-based SAR requires a long integration time to achieve a large synthetic aperture,and the echo signal will be seriously affected by temporal-spatial variant troposphere.Traditional spatiotemporal freezing tropospheric models are ineffective.To cope with this,this paper models and analyses the impacts of temporal-spatial variant troposphere on ground-based SAR imaging of asteroids.For the background tropo-sphere,a temporal-spatial variant ray tracing method is proposed to trace the 4D(3D spatial+temporal)refractive index network provided by the numerical weather model,and calculate the error of the background troposphere.For the tropospheric turbulence,the Andrew power spectral model is used in conjunction with multiphase screen theory,and varying errors are obtained by tracking the changing position of the pierce point on the phase screen.Through simulation,the impact of temporal-spatial variant tropospheric errors on image quality is analyzed,and the simulation results show that the X-band echo signal is seriously affected by the troposphere and the echo signal must be compensated.

Multi-scale object detection by top-down and bottom-up feature pyramid network

While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network(TDBU-FPN),which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes(PASCAL VOC)dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps.

Simulation and Analysis of the Impacts of Anisotropic Ionospheric Scintallition on Geosynchronous Synthetic Aperture Radar

The impacts of ionospheric scintillation on geosynchronous synthetic aperture radar（GEO SAR）focusing is studied based on the multiple phase screen（MPS）theory.The power spectrum density of electron irregularities is first modified according to the ionospheric anisotropy.Then propagation wave equations in random medium are deduced in the case of oblique incidence in GEO SAR.The amplitude and phase errors induced by the random electron fluctuations are generated by the iterated MPS simulations and are superimposed into the GEO SAR signals.Through the following imaging and evaluation,the effects of the anisotropic ionospheric scintallition on GEO SAR are assessed.At last,the optimized integration time under different ionospheric scintillation conditions are recommended through Monte Carlo experiments.It is concluded that,greater ionospheric fluctuations and longer integration time will result in more severe deterioration,even no focus at all in the worst case.

Feasibility study of inclined geosynchronous SAR focusing using Beidou IGSO signals

Dear editor,Geosynchronous synthetic aperture radar(GEO SAR)[1,2]has an inclined geosynchronous orbit of around 36000 km,which leads to its short revisit time of around 24 hours and a wide coverage of up to approximately one third of the Earth surface.Its long integration time guarantees the fine resolution.Thus,GEO SAR owns the promising capability of providing images with the high resolution,

Recent progress in Bistatic SAR with illuminators of opportunity

Bistatic SAR（Bi SAR）with illuminators of opportunity is a kind of flexible SAR system that consists of non-cooperative transmitters and a stationary or moving receiver,as Figure 1shows.In recent years,notable efforts have been made to promote the development of this kind of system.Progress regarding Bi SAR with navigation satellites as transmitters before 2015,including the related theory and practice,has been well reviewed by Antoniou et al.and can be referred from[1].This paper reviews some of the progress in 2015and 2016,including novel signal processing approaches,advanced Bi SAR system configurations and potentially