OBJECT DETECTION FROM SYNTHETIC APERTURE RADAR USING A COMPLEX-VALUED CONVOLUTIONAL NEURAL NETWORK

Abstract: systems and methods are provided for object detection. a radar interface receives complex-valued data representing a region of interest from a synthetic aperture radar system. a complex-valued convolutional neural network includes a plurality of convolutional layers and provides an output indicating if objects are present in the region of interest. each convolutional layer includes a complex-valued kernel that is applied to an input. the kernel includes a first set of weights that is applied to each of real and imaginary components of the input to provide respective first and second convolution products and a second set of weights applied to each of real and imaginary components of the input to provide respective third and fourth convolution products. a difference between the first and fourth convolution products provides a real output component and a sum of the second and third convolution products provides an imaginary output component.

Inventor(s): JOSEPH MOUAWAD, DAVID RILEY ELLIOTT

CPC Classification: G01S13/9023 ({combined with interferometric techniques})

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