后向投影(Back Projection,BP)算法具有精确聚焦、完美运动补偿等优点,适合于机载超宽带合成孔径雷达(Ultra Wide Band Synthetic Aperture Radar,UWB SAR)成像,但是巨大的计算量限制了它的实际应用。子块快速因子分解后向投影算法(Sub-...后向投影(Back Projection,BP)算法具有精确聚焦、完美运动补偿等优点,适合于机载超宽带合成孔径雷达(Ultra Wide Band Synthetic Aperture Radar,UWB SAR)成像,但是巨大的计算量限制了它的实际应用。子块快速因子分解后向投影算法(Sub-Image Fast Factorized Back Projection,SIFFBP)算法大幅度减小了BP算法的计算量,提高了BP算法的实用性。本文通过分析SIFFBP算法区域划分的约束条件,提出了一种基于最优区域划分的改进算法,解决了传统SIFFBP算法在小波束积累角时加速性能下降的问题。当波束积累角小于60度或成像区域长宽相差较大时,改进算法进一步减小了计算量。仿真和实测SAR数据的成像结果验证了改进算法的性能。展开更多
In this paper, we first introduce the situation of Incomplete Factorization(IF)preconditioners. Consequently, we reduce the block tridiagonal matrix with non-singular off-diagonal blocks into a model one that has only...In this paper, we first introduce the situation of Incomplete Factorization(IF)preconditioners. Consequently, we reduce the block tridiagonal matrix with non-singular off-diagonal blocks into a model one that has only negative identity matrixfor its off-diagonals. Then we evaluate the block LU factors for the model with thehelp of M matrices. The analyses show that the evaluation is exact in some sense.For the matrices which have equal diagonal blocks and have only negative identityoff-diagonal blocks, the tendency of the factors are also focused on. Moreover,we construct a type of preconditioners with these evaluations and analyze thecondition number of the preconditioned matrices. For the model problem, we givethe evaluation and practical condition number, which shows that the evaluation isexact to some extent. At last, we implement four of these preconditioners and testthem for the model problem. The results show that our method is effective and theanalyses imply that they will be more efficient than others in parallel computing.展开更多
文摘后向投影(Back Projection,BP)算法具有精确聚焦、完美运动补偿等优点,适合于机载超宽带合成孔径雷达(Ultra Wide Band Synthetic Aperture Radar,UWB SAR)成像,但是巨大的计算量限制了它的实际应用。子块快速因子分解后向投影算法(Sub-Image Fast Factorized Back Projection,SIFFBP)算法大幅度减小了BP算法的计算量,提高了BP算法的实用性。本文通过分析SIFFBP算法区域划分的约束条件,提出了一种基于最优区域划分的改进算法,解决了传统SIFFBP算法在小波束积累角时加速性能下降的问题。当波束积累角小于60度或成像区域长宽相差较大时,改进算法进一步减小了计算量。仿真和实测SAR数据的成像结果验证了改进算法的性能。
文摘In this paper, we first introduce the situation of Incomplete Factorization(IF)preconditioners. Consequently, we reduce the block tridiagonal matrix with non-singular off-diagonal blocks into a model one that has only negative identity matrixfor its off-diagonals. Then we evaluate the block LU factors for the model with thehelp of M matrices. The analyses show that the evaluation is exact in some sense.For the matrices which have equal diagonal blocks and have only negative identityoff-diagonal blocks, the tendency of the factors are also focused on. Moreover,we construct a type of preconditioners with these evaluations and analyze thecondition number of the preconditioned matrices. For the model problem, we givethe evaluation and practical condition number, which shows that the evaluation isexact to some extent. At last, we implement four of these preconditioners and testthem for the model problem. The results show that our method is effective and theanalyses imply that they will be more efficient than others in parallel computing.