基于小波分解与分形内插相结合的地形数据压缩方法

地形匹配制导中需要使用大量的地形数据，因此有效的地形数据压缩技术是非常重要的。传统的地形数据压缩方法主要采用线性内插的方法，但这对于地形起伏较大的山区地形失真太大，不能满足高精度导航的要求。本文基于小波分解与分形内插相结合的方法，提出了一种新的地形数据压缩方法，它具有压缩比高，保真性好，解码快的特点，特别适合山区地形数据的压缩。     

小波变换在遥测信号检测中的应用

为了更好地分析和处理弹载固态记录仪所记载的助推火箭在发射时对弹体的冲击和振动信号，本文利用小波变换所具有的空间局部化性质，在对原始采样数据的奇异性及奇异性位置和奇异度的大小的分析中，以及在导弹型号试射实验的后视数据分析中，取得出了良好的分析效果。     

地磁急始年发生数周期特征的小波分析

采用小波分析方法分析了急始年发生数的时间序列的周期特征，并对急始发生数的特征与太阳黑子相对数的特征进行了简要的对照分析，分析结果表明，急始发生数的周期规律与太阳黑子相对数的周期规律是有差异的．还进行了太阳黑子相对数与急始数的相关性，太阳黑子相对数与急始磁暴的相关性研究，分析结果表明它们之间显著相关．还对急始数与急始磁暴致以及其他的一些参数之间的相关性进行了分析，最后对分析结果进行了讨论．     

Time-series analysis of GPS measurements for long-span bridge movements using wavelet and model prediction techniques

This study aims at assessing the safety behavior of the Incheon long-span bridge using high rate (10?Hz) geodetic monitoring global positioning system (GPS). The time series of wavelet spectrum analysis is utilized to assess the dynamic behavior of the bridge. The coefficients and model errors of the time series autoregressive-moving average (ARMA) model are used to evaluate the movement performances of the bridge. The results show that: (i) the accuracy of GPS measurements to extract the dynamic behavior of the bridge is 97.27% when compared with the design results. (ii) the behavior of the bridge is within the safety limits of the bridge design with minimum observed changes for the historical GPS measurements in time and frequency domains, the mean deflection of bridge deck is 8.26?mm and frequency changes of bridge is 0.004?Hz compared with the design results. (iii) the time series analysis of the wavelet spectrum and ARMA model coefficients can be used to detect the significant frequency changes and study the rigidity of the bridge performance, respectively; and the both methods are found to be suitable techniques to estimate the performance changes of the GPS measurements in the time and frequency domains during the monitoring time period.     

Multi-state autonomous drilling for lunar exploration

Due to the lack of information of subsurface lunar regolith stratification which varies along depth, the drilling device may encounter lunar soil and lunar rock randomly in the drilling process. To meet the load safety requirements of unmanned sampling mission under limited orbital resources, the control strategy of autonomous drilling should adapt to the indeterminable lunar environments. Based on the analysis of two types of typical drilling media (i.e., lunar soil and lunar rock), this paper proposes a multi-state control strategy for autonomous lunar drilling. To represent the working circumstances in the lunar subsurface and reduce the complexity of the control algo-rithm, lunar drilling process was categorized into three drilling states:the interface detection, initi-ation of drilling parameters for recognition and drilling medium recognition. Support vector machine (SVM) and continuous wavelet transform were employed for the online recognition of dril-ling media and interface, respectively. Finite state machine was utilized to control the transition among different drilling states. To verify the effectiveness of the multi-state control strategy, drilling experiments were implemented with multi-layered drilling media constructed by lunar soil simulant and lunar rock simulant. The results reveal that the multi-state control method is capable of detect-ing drilling state variation and adjusting drilling parameters timely under vibration interferences. The multi-state control method provides a feasible reference for the control of extraterrestrial autonomous drilling.     

小波技术在组合导航系统故障诊断中的应用

针对组合导航系统中存在的故障类型和特点，提出一种新的基于信号处理的故障检测方法。该方法利用小波分析技术对含有故障信息的系统信号进行分析处理，并将此方法应用于SINS／GPS组合导航系统。仿真结果分析表明，小波分析技术能很好地及时检测出组合导航系统的硬故障，且更加简便灵活，从而可以将小波分析技术应用于组合导航系统的故障检测。     

Detrend effect on the scalograms of GPS power scintillation

The study of amplitude scintillation on GPS radio links is usually done after detrending the time series of the transmitted power so to define scintillations as the chaotic fluctuation around a unitary value. In a sense, the choice of how to detrend the time series is part of the definition of scintillation.     

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10?Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.     

Characterization of ionospheric amplitude scintillations using wavelet entropy detrended GNSS data

The extensive monitoring networks of Global Navigation Satellite System (GNSS) ionospheric scintillation have been established to continuously log observation data. Further, the amplitude scintillation index and the phase scintillation index, which are derived from scintillation observations, are anticipated to accommodate the accuracy requirement of both the user level and the monitoring station level. However, raw scintillation observations essentially measure superposed waveform impairments of GNSS signals propagating through ionosphere and troposphere. It implies that fluctuations of raw scintillation observations are caused by multiple factors from the entire radio propagation environment. Hence, it is crucial to characterize ionospheric scintillations from GNSS observation data. And the characterization is implemented through extracting fluctuations of raw observations merely induced by ionospheric scintillations. Designed to address this problem by means of Fourier filtering detrending, the present work investigates the influence of varying detrending cutoff frequencies on wavelet statistical energy and wavelet entropy distributions of scintillation data. It consequently derives criteria on the optimum detrending cutoff frequency for three types of raw amplitude scintillation data, which are classified by their wavelet energy distributions. Results of the present work verify that detrending with specific optimum cutoff frequencies rather than the fixed and universally applicable one renders the validity and credibility of characterizing ionospheric scintillations as the part of GNSS observation fluctuations purely induced by ionosphere electron density irregularities whose scale sizes are comparable with or smaller than the Fresnel scale.