Abstract
The authors propose that hidden Markov models (HMMs) and multiaperture synthetic aperture radar (MASAR) imaging can be used to construct automatic target detection algorithms. Their preliminary studies show that HMM MASAR detection: effectively exploits anisotropic scattering differences between target and multiple clutter classes; is computationally efficient; can be used with either single polarisation or multipolarisation SAR imagery; and can be used with either coherent or noncoherent subapertures. Further, the results indicate that the accuracy of HMM MASAR detection is comparable to other techniques while requiring orders of magnitude less computation. These results suggest that the HMM MASAR detection technique could be effectively deployed in fielded automatic target recognition systems.
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