Search

Raw data simulation is the front-end work of synthetic aperture radar(SAR) system development,which is of great significance.For high resolution squint spotlight SAR,time-domain raw data simulation is usually used,but its simulation efficiency is very low.In order to realize the raw data simulation of high resolution squint spotlight SAR efficiently,an effective acceleration algorithm is proposed.To reduce the redundant computation and save memory,this algorithm combines the time-domain raw data simulation model and its signal characteristics to compensate the range cell migration(RCM) in the raw data simulation process of squint spotlight SAR.An adaptive data partitioning algorithm is adopted to compute the partitioned data in graphic processing unit(GPU), and the powerful computing capabilities of GPU is used to improve efficiency.Then the sub data blocks are transmitted and spliced in memory.The proposed algorithm improves the computational efficiency of time-domain raw data simulation,and solves the problems of huge volume of raw data,limited GPU memory and data transmission between video memory and memory.Experimental results of point targets and distributed targets show that the speedup ratio of this algorithm reaches 219.8,which verifies the effectiveness of the proposed method.

Only rarely have polyoxometalates been found to form core–shell nanoclusters. Here, we succeeded in isolating a series of rare giant and all‐inorganic core–shell cobalt polyoxoniobates (Co−PONbs) with diverse shapes, nuclearities and original topologies, including 50‐nuclearity {Co12Nb38O132}, 54‐nuclearity {Co20Nb34O128}, 62‐nuclearity {Co26Nb36O140} and 87‐nuclearity {Co33Nb54O188}. They are the largest Co−PONbs and also the polyoxometalates containing the greatest number of Co ions and the largest cobalt clusters known thus far. These molecular Co−PONbs have intriguing and atomically precise core–shell architectures comprising unique cobalt oxide cores and niobate oxide shells. In particular, the encapsulated cobalt oxide cores with different nuclearities have identical compositions, structures and mixed‐valence Co3+/Co2+ states as the different sized Co−O moieties of the bulk cubic‐spinel Co3O4, suggesting that they can serve as various molecular models of the cubic‐spinel Co3O4. The successful construction of the series of the Co−PONbs reveals a feasible and versatile synthetic method for making rare core–shell heterometallic PONbs. Further, these new‐type core–shell bimetal species are promising cluster molecular catalysts for visible‐light‐driven CO2 reduction. [ABSTRACT FROM AUTHOR]

Only rarely have polyoxometalates been found to form core-shell nanoclusters. Here, we succeeded in isolating a series of rare giant and all-inorganic core-shell cobalt polyoxoniobates (Co-PONbs) with diverse shapes, nuclearities and original topologies, including 50-nuclearity {Co 12 Nb 38 O 132 }, 54-nuclearity {Co 20 Nb 34 O 128 }, 62-nuclearity {Co 26 Nb 36 O 140 } and 87-nuclearity {Co 33 Nb 54 O 188 }. They are the largest Co-PONbs and also the polyoxometalates containing the greatest number of Co ions and the largest cobalt clusters known thus far. These molecular Co-PONbs have intriguing and atomically precise core-shell architectures comprising unique cobalt oxide cores and niobate oxide shells. In particular, the encapsulated cobalt oxide cores with different nuclearities have identical compositions, structures and mixed-valence Co 3+ /Co 2+ states as the different sized Co-O moieties of the bulk cubic-spinel Co 3 O 4 , suggesting that they can serve as various molecular models of the cubic-spinel Co 3 O 4 . The successful construction of the series of the Co-PONbs reveals a feasible and versatile synthetic method for making rare core-shell heterometallic PONbs. Further, these new-type core-shell bimetal species are promising cluster molecular catalysts for visible-light-driven CO 2 reduction., (© 2023 Wiley-VCH GmbH.)