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The Radar Cross Section (RCS) prediction for cavities is significant to measure a target's radar detection ability. For electrically large, deep, arbitrary shaped cavities, this paper presents a hybrid algorithm based parallel solution using Message Passing Interface on distributed memory computers. The meaning of `Hybrid' here is threefold. First, the RCS for cavities is modeled and calculated with a hybrid algorithm of IPO (Iterative Physical Optics), FMM (Fast Multipole Method) and Generalized Reciprocit Integral (GRI) combined by a cascading segmentation technique. Second, a hybrid approach is applied to the two phases of parallelization. On phase of geometrical preprocessing, all parallel processes assume a whole workload to construct the cavity geometry independently. On the other phase of electromagnetic computing, the workload is distributed by domain decomposition. Third, the decomposition scheme is hybrid as facets are decomposed to compute near-field interation while angle samples are used to distribute far-field interaction. The superposition of electromagnetic measures and permutability of math vector operations are fully exploited to do partial computation in order to minimize the communication overhead. The hybrid parallel solution can achieve very good tradeoff between memory and time. It yields a good load balance while still keeping the parallel code pretty concise. Numerical results show near-linear scalability and over 90% parallel efficiency.
}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/636.html} }The Radar Cross Section (RCS) prediction for cavities is significant to measure a target's radar detection ability. For electrically large, deep, arbitrary shaped cavities, this paper presents a hybrid algorithm based parallel solution using Message Passing Interface on distributed memory computers. The meaning of `Hybrid' here is threefold. First, the RCS for cavities is modeled and calculated with a hybrid algorithm of IPO (Iterative Physical Optics), FMM (Fast Multipole Method) and Generalized Reciprocit Integral (GRI) combined by a cascading segmentation technique. Second, a hybrid approach is applied to the two phases of parallelization. On phase of geometrical preprocessing, all parallel processes assume a whole workload to construct the cavity geometry independently. On the other phase of electromagnetic computing, the workload is distributed by domain decomposition. Third, the decomposition scheme is hybrid as facets are decomposed to compute near-field interation while angle samples are used to distribute far-field interaction. The superposition of electromagnetic measures and permutability of math vector operations are fully exploited to do partial computation in order to minimize the communication overhead. The hybrid parallel solution can achieve very good tradeoff between memory and time. It yields a good load balance while still keeping the parallel code pretty concise. Numerical results show near-linear scalability and over 90% parallel efficiency.