Liu Xuebin

Interferogram spectrum reconstruction using modern spectral estimation

In this paper, we first discussed basic spectral estimation concepts and algorithms, then pointed out that the conventional spectrum reconstruction algorithm is virtually the same with Blackman-Tukey (BT) algorithm in spectral estimation. Then we use two different method (Auto-Regressive parametric model and eigenvector spectral estimation method) to reconstruct light spectrum from interferogram, and compared the results with conventional method for spectrum reconstruction. From the comparison we concluded that the modern spectrum estimation methods can well be adopted in Fourier Transform (FT) spectrum reconstruction and would perform excellent, especially when to get higher spectrum resolution from a short series of data recorded. Later we discussed the disadvantages and restrictions of the two methods used in the simulation. From these results and discussions, we suggested to implement various new spectral estimation method in FT spectrum reconstruction to get better performance.

Implementation of a LMS filter on FPGA employing extremeDSP and smart IP-core design

Field Programmable Gate Arrays have become popular platform for digital signal processing, however, the conventional method, which is essentially writing a source code in a hardware description language to design a product on a FPGA, is time consuming and complicated. This restricts the implementation of complex signal processing algorithm on FPGA. In this paper, two fast design methods of algorithm implementation on FPGA were proposed: ExtremeDSP solution and Smart IP-Core technology. The AccelDSP Synthesis tool, as the main component of ExtremeDSP solution allows transferring a MATLAB floating point design into a hardware module that can be implemented on a Xilinx FPGA. Employing predefined cores can cut the design time and significantly reduce risk while having access to the best performing and lowest cost component available. Implementation of a LMS-adaptive filter employing these two methods has been achieved and the simulation results indicate that both of the two fast designs have high performance.

Centroid registration difference algorithm for detecting spatial moving targets

In order to meet the needs of recognizing the targets under the moving space background by micro spacecraft target detector (MTD). According to the particular characters of the spatial background, this paper proposes an algorithm which combines the image centroid registration with the single difference method, named the Centroid Registration Difference Algorithm. In this algorithm, we labeled only the available bright sign spots and has distilled its centroid in two frames, and then used the image centroid registration to compare the two images and eliminated the same light spots between them, then the remaining bright spots in the present image were our targets. The simulation results indicate that the proposed algorithm has a low computational cost and the effect of the recognition is good.

Experiment Research and Analysis of Spectral Prediction on Soil Leaking Oil Content

The spectral analysis method was applied experimentally to extract the spectral indices, measure and analyze the spectral characteristics and their difference of the mixture which are composed in soil in Central Shaanxi Plain and the diesel and motor oil respectively, aiming to provide solutions to practical difficulties in detecting, analyzing the spectral characteristics and difference between the soil leaking with equal content diesel and motor oil and predicting the leaking content of diesel in the soil. The spectral response curves of the soil leaking with different oil respectively and the soil leaking with diesel with different content were collected. Then the spectral prediction model for the leaking content of diesel in the soil was built based on the reflectance characteristics. The coefficient of the detection (R-2) was introduced to evaluate the stability of the built model, and the parameter root mean squared error (RMSE) was introduced to estimate the precision and the predictability of the model built in this work. It is demonstrated that : (1) The reflectance of soil leaking with diesel is less than that of the equal content motor oil. And there is a double absorption trough of the reflectance curve of both soil leaking with diesel and motor oil at 1 740 and 2 328 nm. The spectral absorption indices and absorption depth of the soil leaking with diesel keep less than the equal content motor oil. (2) The built spectral prediction model for the leaking content of diesel in the soil demonstrates good stability with the coefficient of determination at R-2 = 0. 854, and performs favorable predictability (Root-Mean-Square Error, RMSE=0.016), which can benefit the effective prediction and quick estimation methods of the leaking content of diesel in the soil, enrich and progress the experimental method and theoretical research work of spectral prediction on soil leaking oil content and promote the application of remote sensing in safety production and environmental protection.