Due to existence of the long along-track baseline (ATB) among the different satellites in a distributed space-based radar (DSBR) system, a large number of grating lobes appear in radar returns, causing the non-continuous detection phenomenon of an air moving target (AMT). To solve this problem, in this paper, a novel approach for ATB distribution design in a DSBR system is proposed. In the proposed algorithm, to reduce the amount of spatial ambiguity points located at the main-lobe region and achieve the best air moving target indication (AMTI), the maximum target detectability ratio (TDR) in the main-lobe region is chosen to be the criteria for the optimal ATB design. The effectiveness of the proposed method is verified by the simulated multi-channel radar data in a DSBR system.

Mosaic mode synthetic aperture radar (SAR) combines the spotlight or sliding spotlight mode with a ScanSAR mode to accomplish the high azimuth resolution and large imaging swath SAR imaging. This paper studies the problem of the frequency modulated continuous wave (FMCW) SAR imaging with a Mosaic mode, where the imaging algorithms for pulse radars are not suitable for a FMCW SAR. To deal with this issue, this paper proposes a FMCW Mosaic mode SAR imaging algorithm based on modified polar formation algorithm (PFA), which considers the radar motion during the signal transmission and performs the SAR imaging operation for spotlight mode in each Mosaic unit. The simulation results of point targets verify the effectiveness and feasibility of the proposed method, which may provide a valuable reference for the application of Mosaic system to miniaturized platforms.

Compared with a monostatic inverse synthetic aperture radar (ISAR) imaging system, a bistatic ISAR (Bi-ISAR) system offers more comprehensive target information, along with higher system security and resistance to interference. However, the inherent geometric configuration of Bi-ISAR will introduce the linear-geometry distortion (LGD), causing the target to appear sheared in shape and impacting subsequent target recognition. To deal with this issue, in this paper, a novel deep learning-based algorithm is proposed to realize the LGD correction. In the proposed algorithm, a neural network called DoubleUNet is employed for the accurate semantic segmentation of target's ISAR image. Then the initial target ISAR image is transformed into two-dimensional point clouds based on the estimated radar parameters. Finally, the linear coupling relationship between azimuth and range dimensions is removed, beneficial to the target ISAR shape restoration and subsequent recognition. Simulation experiments validate the proposed algorithm.

The passive microwave observations from geostationary earth orbit (GEO) are able to enhance the short-time forecasting of tropical cyclones (TCs) due to its ability to track and detect the internal structure of TCs. To assess the operational capabilities of the candidate GEO microwave instruments, the numerical simulations of GEO microwave observation for the three TC cases were carried out. This paper compares the abilities of 3 candidate passive microwave sensors, based on GEM/GOMAS, GeoSTAR and GIMS-II respectively, to observe the upwelling brightness temperatures of TCs at 50-57GHz band. The analysis is based on WRF model variables and radiative transfer mode DOTLRT.

To assimilate satellite-based passive microwave observation over heavy clouds and precipitation into numerical weather prediction (NWP) systems and thus to improve the performance of it has become an intensely studied topic. These attempts rely on the development of a radiative transfer (RT) model that accounts for particle scattering and accurately simulates the observation process at an acceptable computational speed. In this paper, two existing RT models (the RTTOV and the DOTLRT) are tested and the accuracies are evaluated by comparing the simulated brightness temperature with real observational data of a satellite-based sounder ATMS. RTTOV is much more well-known and widely applied, however, since these two models use different solvers to deal with the scattering effect, whether it is possible to improve the performance of RT model is still open to discussion.