Raman spectroscopy provides information about the structure, functional groups and environment of the molecules in the samples, and is widely used in various application areas including chemical analysis, biological processes, environmental and food sciences etc., because of its features of rapidness and non-destruction. The processing and analysis of Raman spectrum is required to extract useful information from original spectrum. For each individual spectrum, a multitude of preprocessing algorithms are required to eliminate effects of unwanted signals such as fluorescence, Mie scattering, detector noise, calibration errors, cosmic rays, laser power fluctuations, and other distortions. Among common methods, Moving Window Average, Moving Window Median and Savitzky-Golay (SG) filter require to set the length of the window, Wavelet based method requires to choose the appropriate Wavelet family, thresholds, and scales, thus the methods mentioned above is not applicable for fully automated data processing and qualitative analysis of handheld Raman spectroscopy. This paper proposes a multi-scale wavelet thresholding denoising algorithm (MWTD). The Raman signal is decomposed into different scales (multi resolution), each scale (resolution) gives different frequency-related information contained in the Raman signal. As noise (high frequency) related frequencies are different compared with genuine Raman bands (mid frequency), at an optimum resolution appropriate thresholds can be applied to eliminate noise. After thresholding (removing) the noise, the corrected Raman signal can be obtained by the Inverse Wavelet Transform. Both simulated and experimental data are used to evaluate the performance of the MWTD algorithm. The results demonstrate that the proposed MWTD method is superior to the hard/soft threshold and Savitzky-Golay (SG) methods in improving SNR, and can effectively eliminate the spectral noise and retain important detail features in the signal. When processing large datasets, a fully automated algorithm such as MWTD would be desirable as it is not required to set any parameters. Thus, the proposed MWTD method is more suitable for the preprocessing before the spectral data modeling and has a better application in the spectroscopic analysis.
The threat of the IR guidance missile is a direct consequence of extensive proliferation of the airborne IR countermeasure. The aim of a countermeasure system is to inject false information into a sensor system to create confusion. Many optical seekers have a single detector that is used to sense the position of its victim in its field of view. A seeker has a spinning reticle in the focal plane of the optical system that collects energy from the thermal scene and focuses it on to the detector. In this paper, the principle of the conical-scan FM reticle is analyzed. Then the effect that different amplitude or frequency modulated mid-infrared laser pulse acts on the reticle system is simulated. When the ratio of jamming energy to target radiation (repression) gradually increases, the azimuth error and the misalignment angle error become larger. The results show that simply increasing the intensity of the jamming light achieves little, but it increases the received signal strength of the FM reticle system ,so that the target will be more easily exposed. A slow variation of amplitude will warp the azimuth information received by the seeker, but the target can’t be completely out of the missile tracking. If the repression and the jamming frequency change at the same time, the jamming effects can be more obvious. When the jamming signal’s angular frequency is twice as large as the carrier frequency of the reticle system, the seeker will can’t receive an accurate signal and the jamming can be achieved. The jamming mechanism of the conical-scan FM IR seeker is described and it is helpful to the airborne IR countermeasure system.