Objects recognition in high-scattering conditions at radio/microwave frequency

This paper introduces an innovative technique for object recognition in environments characterized by high-scattering conditions, leveraging radio and microwave frequencies. The method integrates the angular spectrum of diffracted and scattered components into Fresnel Coherent Diffraction Imaging, enabling real-time digital recording of distribution patterns. Traditional approaches often grapple with limitations imposed by minimum pixel size, which this technique overcomes through the application of digital holography. Here, imaging resolution is dictated by minimum phase measurements and signal sampling steps. Long-wavelength radio frequency signals, recognized for their exceptional penetration capabilities, are harnessed for high-resolution detection and recognition. The diffraction components offer valuable insights into an object's dielectric properties, size, and shape. Importantly, this information remains invariant to the object's spatial position when radio and microwave wavelengths significantly exceed the object's size. The integration of monopulse multi-channel signal processing with Software Defined Radios plays a pivotal role in substantially reducing computational complexity for object recognition. The application of simple onestep algorithms enhances efficiency in decision-making processes. This proposed technique marks a promising advancement in overcoming challenges associated with object recognition in high-scattering conditions, promising improved resolution, and computational efficiency.