In high resolution remote sensing satellite imaging system, image restoration is an important step to visualize
ne details and mitigate the noise. The raw image data often presents poor imaging quality due to various
reasons and Point Spread Function (PSF) measures such blurriness characteristic of the image using point
source. Satellite image from Korea Multi-purpose Satellite 2 (KOMPSAT-2) also requires Modular Transfer
Function (MTF) compensation process to achieve more realistic image which entails removing ringing artifacts
at the edges and restraining excess use of denoising eect in order to keep it more realistic. This paper focuses
on the deconvolution of KOMPSAT-2 image utilizing PSF attained from Korea Aerospace Research Institute
compared to deconvolution with the estimated PSF blur kernel. The deconvolution algorithm considered are
Richard-Lucy, Damped Richard-Lucy, Bilateral Richard-Lucy and Sparse Prior deconvolution algorithms.
In this paper, we propose new convolutive source separation and selective null beamforming methods using a pilot-based channel estimation technique in reverberation environments. First, we show convolutive sound source separation methods in determined and overdetermined cases. For the acoustic channel estimation, we propose a new channel estimation method using pilot sequence conceptually similar to a pilot code in wireless communication. Pilot sequence is composed of sum of sinusoidal sequences at frequencies matching STFT (Short-Time Fourier Transform) frequencies. Proposed channel estimation method considered the effect of spectral sampling with frequencies matching STFT frequencies provides precise channel information we want to know and has less computational loads than other competitive methods. After acoustic channel estimation, we can separate the signals from observations using inverse(or pseudo-inverse) operator of estimated channel matrix at each frequency bins. We show the proposed method has better performance than other competitive methods in various measures. Second, we propose selective null beamforming using a pilot-based channel technique. If we use same pilot sequence at each transmitter, we can obtain relative difference of acoustic channel between transmitters as well as between microphone array. From estimated channel information, we can calculate beamforming weight vectors to null the signals at target location and to transmit the signals to desired location without distortion using singular value decomposition at each frequency bins. We evaluate the performance of proposed methods through experiments as well as the computer simulations.
KEYWORDS: Radar, Doppler effect, Target detection, Antennas, Signal processing, Detection and tracking algorithms, Signal generators, Radar signal processing, Signal detection, Digital signal processing
We describe a flexible hardware system of the Doppler radar which is designed to verify various baseband array signal processing algorithms. In this work we design the Doppler radar system simulator for baseband signal processing in laboratory level. Based on this baseband signal processor, a PN-code pulse doppler radar simulator is developed. More specifically, this simulator consists of an echo signal generation part and a signal processing part. For the echo signal generation part, we use active array structure with 4 elements, and adopt baker coded PCM signal in transmission and reception for digital pulse compression. In the signal processing part, we first transform RF radar pulse to the baseband signal because we use the basebands algorithms using IF sampling. Various digital beamforming algorithms can be adopted as a baseband algorithm in our simulator. We mainly use Multiple Sidelobe Canceller (MSC) with main array antenna elements and auxiliary antenna elements as beamforming and sidelobe canceller algorithm. For Doppler filtering algorithms, we use the FFT. A control set is necessary to control overall system and to manage the timing schedule for the operation.
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