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As an important equipment for deep space soft landing, microwave radar provides range and velocity for the probe. Accuracy and operational envelope of range and velocity are key design indexes for landing radar, at the same time, it must be small, lightweight and reliable for deep space exploration. The performance, tested both on ground and in orbit when landing on the moon, is excellent. Based on the telemetry of Chang'e 3 and Chang'e 4 probe, reflectivity of moon surface can be gotten, this will be useful for future detection and microwave radar design.

In this paper we propose a new polarimetric calibration method for C-band spaceborne SAR based on scattering model of amazon rainforest. The well-known Freeman-Durden model is used to express the polarimetric scattering mechanisms of amazon rainforest for C-band spaceborne SAR, and then nonlinear equations with polarimetric distortion parameters are built by use of covariance matrix and solved iteratively to get the polarinetric distortion matrix (PDM). In comparison with the Quegan method, no approximation is used in our method and therefore we can solve all the polarimetric distortion parameters more accurately, even if the crosstalk is high. Moreover, both channel imbalances and crosstalks can be directly estimated by our method, which is more practical as no artificial reflectors are needed to determine the channel imbalances. Simulations based on the RADARSAT-2 data confirm the validity and feasibility of the proposed method.

It is well known that digital beamforming (DBF) is powerful technique to handle the conflict between high spatial resolutions and large swath width for Spaceborne SAR system based on multi-beam reflect-array antenna. The DBF technique can effectively suppress the interference (with different incoming elevation angle) caused by range ambiguity while maintain the gain on desired elevation direction. However, a performance degradation of the DBF will be occurred when geometry between the satellite and earth is uncertain. In this paper, the performance degradation caused by the uncertain geometry between the satellite and earth is analyzed. To overcome the performance degradation due to elevation angle mismatch, a robust DBF method for spaceborne SAR system is proposed. Our method can widen the null in receive beampattern to reduce the performance degradation due to angle mismatch.

Chang’E-3 successfully landed at the north part of the Mare Imbrium on 14 December 2013 and Chang’E-4 landed at South Pole’s Aitken Basin on 3 January 2019. During the powered descent phase, information on the position and velocity of the landers relative to the Lunar surface is provided by the microwave range and velocity sensor, a radar system developed specifically for the Chang’E missions. Values of the Lunar surface backscattering coefficient are an important basis for designing the microwave range and velocity sensor system. In this paper, we firstly have estimated the Lunar surface backscattering coefficient according to the real measured data of the microwave range and velocity sensor in Chang’E-3 and Chang’E-4 mission. Then a scattering model based on Kirchhoff Approximate (KA) is established to simulate the Lunar surface backscattering coefficient. The agreement of the simulated and measured results have proved the effectiveness of Lunar surface backscattering model based on the KA and the resulted backscattering coefficient values could provide significant reference for future Lunar detection missions.

Radio frequency interference (RFI) suppression has become an essential step in synthetic aperture radar (SAR) imaging processing. In this paper, a spectral filling filtering method for RFI suppression referred to notch filter is derived and analysed. The derivation results show the reason for the “residual terms” after suppression processing in frequency domain and the influence of the “residual terms”. And a conclusion is drawn: the essence of interference suppression based on spectral filling filter is the dynamic change process of “residual terms”. Since they cannot be completely eliminated in theory, they will affect the image quality after interference suppression, but the effect of spectral filling method is better than that of the notch filter method. The conclusion is verified by the simulation experiment.

Electromagnetic scattering characteristics of house vary with different viewing directions. Due to the complex structure, such as facets, edges and corners, only parts of the house features are attainable under a certain observation angle in synthetic aperture radar (SAR) imagery. Since structure features are important for target detection and recognition, collecting more target features is great benefit for SAR application. In this paper, a new method of house structure feature enhancement using SAR images acquired in multi-view directions is proposed. By combining the images of targets of interest at different view angles, the aggregate radar scattering image is produced, which greatly facilitates structure interpreting. Results are presented with SAR images acquired by an airborne sensor, showing the promising performance of the method.

Intensive research is currently concentered at the field of Space-borne Reflector Synthetic Aperture Radar (SAR) Systems for high resolution wide-swath application. To meet the requirement of high resolution wide-swath SAR system, multichannel systems based on Reflector SAR system is introduced, for example, Tandem-L/NISAR Mission. This paper introduces an air-borne SAR system based on Reflector SAR system, and takes several flight experiments. The results show that using Digital beam forming (DBF) algorithm, a simultaneous improvement in azimuth resolution and wide swath can be achieved.

We propose a Non-Local despeckling approach by using the new pixel-relativity measure, based on ratio distance, and thresholding the pixel-similarity. Firstly, the pixel-relativity model based on ratio distance is obtained by transforming the joint probability density function of two pixels having the same reflectivity. Then a table of pixel-similarity threshold, as a function of the SAR image look number and neighboring reflectivity ratio, is trained according to the minimum error probability criterion. Finally, the pixel-similarity threshold is used to select similar pixels from the searching window for real reflectivity estimation. The proposed approach is verified by the comparison with PPB and LHRS-PRM filters using synthetic and real SAR images. The visual quality and the quantification comparison show that our method is excellent in restoring not only the uniform area but also the borders and texture area. (6 pages)