Passive Millimeter Wave Image Super Resolution Reconstruction Algorithm And The Realization Of Dsp

Passive millimeter-wave (PMMW) imaging system receives radiation energy differences of the objects in the millimeter wave band to achieve imaging. Compared with the optical or X-ray imaging technology, because of its strong penetrating, no radiation and concealment, PMMW imaging has an unparalleled advantage in the field of the military reconnaissance, aviation security and the counter-terrorism. It has become a hot topic of research at home and abroad.Super-resolution recovery is a key technology for passive millimeter-wave imaging signal processing. It can restore the high-frequency information lost by the low-pass effect of the imaging system, to improve the resolution of the imaging system.This paper focuses on passive millimeter-wave image super-resolution restoration and DSP implementation. The main contents are as follows:1. Comparative analysis the super-resolution recovery algorithms based on statistical optimization theory, including Richardson-Lucy algorithm, projection Landweber algorithm, image space reconstruction algorithm and so on. Estimate computational complexity of the algorithms to lay the foundation for DSP implementation of the super-resolution algorithms.2. Propose an adaptive regularization super-resolution algorithm based on PCA and wavelet decomposition, effective use of a priori information of the millimeter-wave image, better recovery results than the traditional super-resolution algorithm.3. Based on the ADSP TS-201hardware platform, accomplish the design of the real-time signal processing unit of the PMMW imaging system, achieving the functions of data transmission communication, image preprocessing which includes calibration channel correction, image data rearrangement and channel equalization to remove stripe noise, and the super-resolution image recovery function library.4. Accomplish the joint commissioning of the PMMW imaging system; accomplish the field imaging experiments with single and multi channel for a variety of objectives and scenarios.At last, the simulations and experiments validate the effectiveness of the adaptive regularization super-resolution algorithm based on PCA and wavelet decomposition and the signal processing unit functions of the PMMW imaging system.