Architecture design of GPS software receiver and implementation of its acquisition algorithm with fine frequency estimation

The design of a global positioning system （GPS） software receiver is introduced. This design uses the concept of software radio, and it consists of the following parts： front-end, acquisition, tracking, synchronization, navigation solution and some assisting modules. In the acquisition module, the acquisition algorithm based on circular correlation is utilized. The input data and the local code are converted into the frequency domain by means of the fast Fourier transform （FFT）. After performing circular correlation, the initial phase of the C/A code can be obtained and the cartier frequency can be found in 1 kHz frequency resolution, which is too coarse to use for the tracking loop. In order to improve the frequency resolution, the fine frequency estimation through a phase relationship is then achieved, by which, the frequency resolution is improved dramatically. Experiments show that the inaccuracy of the carrier frequency can be estimated within a few hertz by the fine frequency estimation method, and the fine frequency attained can be directly used for the tracking loop.

Statistical analysis of fracture properties based on particle swarm optimization and Pearson correlation coefficient method

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.

基于主元分析的随机相移散斑图分析算法

剪切散斑相移干涉术需要提取物体加载后的动态相位变化,因此提出一种基于主元分析的随机相移散斑图分析算法。该算法采用相关计算法从随机相移散斑图中获得随机相移条纹图,然后利用主元分析算法(PCA)从一组随机相移条纹图中提取动态相位分布。实验结果表明,相关计算法处理散斑图所得的随机相移条纹图具有较高信噪比,PCA提取的相位具有较高的精度和效率。该算法无需迭代计算,对随机相移条纹图的空间载波频率没有严格的要求,适合动态剪切散斑干涉测量。

Convergence and error estimate of cascade algorithms with infinitely supported masks in L_p(R^s)

The cascade algorithm plays an important role in computer graphics and wavelet analysis.In this paper,we first investigate the convergence of cascade algorithms associated with a polynomially decaying mask and a general dilation matrix in L p (R s) (1 p ∞) spaces,and then we give an error estimate of the cascade algorithms associated with truncated masks.It is proved that under some appropriate conditions if the cascade algorithm associated with a polynomially decaying mask converges in the L p-norm,then the cascade algorithms associated with the truncated masks also converge in the L p-norm.Moreover,the error between the two resulting limit functions is estimated in terms of the masks.

Transverse flowmetry of carbon particles based on photoacoustic Doppler standard deviation using an auto-correlation method

In order to measure the flow velocity of carbon particle suspension perpendicular to the receiving axis of ultrasound transducer, the standard deviation of photoacoustic Doppler frequency spectrum is used to estimate the bandwidth broadening, and the spectrum standard deviation is calculated by an auto-correlation method. A 532 nm pulsed laser with the repetition rate of 20 Hz is used as a pumping source to generate photoacoustic signal. The photoacoustic signals are detected using a focused PZT ultrasound transducer with the central frequency of 10 MHz. The suspension of carbon particles is driven by a syringe pump. The complex photoacoustic signal is calculated by Hilbert transformation from time domain signal before auto-correlation. The standard deviation of the Doppler bandwidth broadening is calculated by averaging the auto-correlation results of several individual A scans. The feasibility of the proposed method is demonstrated by measuring the spectrum standard deviation of the transversal carbon particle flow from 5.0 mm/s to 8.4 mrn/s. The experimental results show that the auto-correlation result is approximately linearly distributed within the measuring range.

On the complexity of average path length for biological networks and patterns

Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length （APL） of a graph requires traversing all nodes in the graph repeatedly, which is computationally expensive for graphs containing large number of nodes. We propose a novel method to calculate APL for graphs commonly required in the studies of genetics. The proposed method is computationally less expensive and less time-consuming compared to standard method.