Role of parallelism in wavelet analysis of radar imaging

Abstract

The continuous wavelet analysis method developed by J. Bertrand, P. Bertrand and J. P. Ovarlez [14] represents target reflectivity by a function on a space with four dimensions, commonly called radar hyperimage. It represents a theoretical formulation of radar imaging that is an improvement and an extension of the tomography technique developed by C. Pouit [2] in the 1970s. The hyperimage is becoming a new tool for perceiving microwaves, an interface between radar and the eye, providing the representation of the information contained in all the radar measurements, also called hologram. The hyperimage is easily constructed by an efficient, original algorithm that uses fast computation tools based on fast Fourier transforms (FFT). The computation load is however large and the execution time required by the method on a sequential computer is prohibitive. However, the structure of the algorithm naturally gives the idea of implementing it on a multiprocessor machine. Our work shows that programming the algorithm on a parallel computer makes it possible to approach real time performance and make the software interactive. In effect, the performance of our HYPIM programme developed on ONERA's iPSC860 has demonstrated that the combined use of the many facilities offered by wavelet analysis and by parallel computation improves the capabilities of radar imaging.