The Study Of Signal Processing And Image Restoration For Magnetic Force Resonance Microscopy

Magnetic resonance force microscopy(MRFM)is a three-dimension imaging instrument which can achieve nanometer resolution for molecules.By subtly combining the technology of magnetic resonance imaging and the technology of scan probe microscopy,MRFM possesses both three-dimension detection capacity of magnetic resonance imaging and high spatial resolution of scan probe microscopy,therefore MRFM is capable of detecting single spin of unclear.However,MRFM have the problems such as slow scan speed,sensitive to noise and slow imaging speed,the solution of these problems lies in the usage of effective and subtle signal processing methods and image processing methods.This thesis studied some signal processing methods and image processing methods that MRFM involves,including four sections:the parameters estimation of noisy sine signal,the application,of ARMA model in system identification for micro-cantilever,and the restoration of sample's spin density image(SPI).The primary research works and innovative are as follow:(1)This thesis studied the parameters estimation of noisy sine signal.We employ segmented maximum likelihood estimation to estimate both amplitude and phase of noisy sine signal accord to the statistical properties of signal's noise.Simulation result demonstrates that the estimated error's variance of estimate algorithm is pretty closeto Cramer-Rao lower bound,and therefore the estimation algorithm we studied iswell-performing.(2)We employ system identification and modal parameters identification tomicro-cantilever via ARMA model in order to knowing the modal information of micro-cantilever.Aiming at the problem that observing noise will decrease theidentification accuracy of time series model,we studied the problem of converting theARMA model with observing noise to the ARMA model without observing noise.After obtaining micro-cantilever's ARMA model,this model is converted to a transfer function of continual system,and then micro-cantilever's modal parameters were calculated from the transfer function.A recovery filter is constructed on the basis of the model obtained by system identification in order to decrease the delay time of micro-cantilever response to external force.The applied force signal is output by inputting displacement signal into the recovery filter.Simulation result and experimental result show the effectiveness of system identification,modal parameter identification and signal recovery method presented by this thesis.(3)This thesis studied the imaging mechanism of MRFM and the restoration method of SPI in order to restore the SPI from degrade image.The expression of point spread function(PSF)is derived according to MRFM's imaging mechanism.Considering the ill-conditioned of image restoration problem,when PSF is easily to obtain,we employ non-blind image restoration algorithm based on sparse restraint to tactic image restoration task,otherwise a blind image restoration algorithm that can restore PSF and SPI simultaneously is employed instead.(4)A scheme that conducts spread spectrum to input signal and conducts de-spreading to output signal is proposed to enhance the anti-jamming capacity of MRFM.The anti-jamming capacity of this scheme is investigated by using the theory of signal processing.We discovered that under certain conditions the anti-jamming capacity of proposed scheme is better than the scheme that spread spectrum is not imposed.Simulation result shows the effectiveness of proposed scheme.