基于到达时间量测的多传感器协同定位算法研究

针对基于到达时间量测的多传感器协同目标定位问题,研究不同准则下的解析算法和数值迭代算法,并分析比较了它们各自的优缺点。首先,通过对原始的高斯-牛顿算法进行修正,改善了数值迭代算法在量测噪声强度较大情况下算法的估计效果。随后,利用热图分析了两类算法在不同目标位置时的估计效果差异。最后,在不同噪声强度下对比了多种算法的估计效果,分析了不同算法效果差异存在的原因以及适用条件。研究结果能够对不同场景下如何选择定位算法提供建议。

一种快速星光角距/时间延迟量测组合导航方法

基于太阳震荡的时间延迟是一种新型天文导航量测量,将其与星光角距量测量结合,可以提高导航性能。然而,火卫一的星历误差将降低导航精度。针对这一问题,提出了一种快速星光角距/时间延迟量测组合导航方法,在线估计火卫一的位置和速度,抑制火卫一星历误差对星光角距/时间延迟量测组合导航估计精度的影响,并引入事件触发机制,通过设定阈值对新息(innovation)的幅值进行检验,选择性地进行基于时间延迟的隐式无迹卡尔曼滤波。仿真结果表明,提出的方法可以在保证导航精度的前提下,比在线估计运行的天文测角/时间延迟量测组合导航方法耗时减少约90%,有效提高了导航实时性,可为火星导航提供技术支持。

考虑星历误差的天文测角/时间延迟量测组合导航方法

基于太阳振荡的时间延迟是一种新型天文导航量测量,可以提供探测器相对反射天体的距离信息,与星光角距量测量结合,可以提高导航性能。然而,星光角距量测模型与时间延迟量测模型均含有火卫一相对火星的位置矢量,火卫一的星历误差将影响导航精度。针对这一问题,提出了一种基于在线估计的天文测角/时间延迟量测组合导航方法,建立了包含火卫一位置及速度的状态模型,利用星光角距及时间延迟量测量同时对火卫一的位置和速度进行在线估计。仿真结果表明,提出的方法可以有效抑制火卫一星历误差对组合导航精度的影响,为探测器提供高精度的自主导航信息。

基于时间错序量测的多目标多传感器跟踪算法研究

在多传感器多目标跟踪系统中,经常有来自同一目标的量测到达融合中心时存在时间先后顺序上的混乱,被称为时间错序量测(Oosm);通常,现有的跟踪算法都是假设理想目标的观测值不混乱;现实中,可能错过的目标探测随意混乱,因而,滤波器不得不处理起因未知的量测,那么针对顺序量测的传统滤波器,例如KF,在此就不能直接使用;通过基于一些特殊矩阵非单一假设的经济存储和能效估计介绍了全局最优Oosm刷新算法,并结合概率数据关联PDA到Oosm刷新算法中;仿真结果显示Oosm刷新的PDA滤波器在性能上优于忽略Oosm的PDA滤波器,还就关于杂波中多目标跟踪如何通过JPDA结合oosm刷新算法展开讨论。

传统民宅戏楼声学特性测量

A comprehensive acoustical test was conducted in the traditional Ch ine se in-house theater, the theater of Shi`s residence in Tianjin. The measured pa rameters include reverberation time, clarity, lateral reflectance and IACC. Prim ary analysis was done with the test result.

通信系统仿真中估计正弦信号信噪比的新方法

正弦信号在通信系统中应用非常广泛,对其信噪比进行估计有着重要的意义,许多算法都需要以此获取最优性能。本文提出了在通信系统仿真中采用FFT估计正弦信号信噪比的新方法,并分析了信号频点数、采样率及量测时间对估计结果的影响。仿真结果表明,该方法能够正确地估计信噪比,通过合理的参数设置,误差均值可达0.3 dB以下。

多传感器异步融合方法研究

在多传感器目标跟踪系统中,使用多个具有不同速率异步传感器观测效果,优于采用具有同样传感器个数的同步传感器的跟踪系统。本文讨论了为解决此类跟踪问题而提出的一系列多传感器异步跟踪算法,并对所提及的算法进行分析比较。为在异步目标跟踪系统中融合方法的取舍提供了依据。

Precise measurement method of optical fiber length based on timestamp technique

A measurement method of optical fiber length using timestamp technique is demonstrated. Based on IEEE1588 precise clock synchronization protocol, the principle that time delay asymmetry on two path results in synchronization time deviation is used, and the difference between two-path delays could be deduced by measuring the synchronization time deviation reversely. Then the length of optical fiber on one path could be calculated if that on the other path is known Due to the fact that the path of Sync and Delay_Req message is symmetric, the optical pulse dispersion and the asymmetry of photoelectric detector performance on two paths are averaged by exchanging two optical fibers. The time difference between master and slave clocks is eliminated by sharing the same time base. At last, the lengths of two single-mode optical fibers are measured with the uncertainty of 0. 578 m for 3 227. 722 m and 0. 758 m for 25 491. 522 m, respectively. Thus this method has high precision and long range.

Diurnal Variation of Soil CO2 Efflux and Its Optimal Measuring Time-window of Temperate Meadow Steppes in Western Songnen Plain, China

In order to study the diurnal variation of soil CO2 effiux from temperate meadow steppes in Northeast China, and determine the best time for observation, a field experiment was conducted with a LI-6400 soil CO2 flux system under five typical plant communi- ties （Suaeda glauca （Sg）, Chloris virgata （Cv）, Puecinellia distans （Pd）, Leymus chinensis （Lc） and Phragmites australis （Pa）） and an alkali-spot land （As） at the meadow steppe of western Songnen Plain. The results showed that the diurnal variation of soil CO2 effiux exhibited a single peak curve in the growing season. Diurnal maximum soil respiration （Rs） often appeared between 1 1：00 and 13：00, while the minimum occurred at 21：00-23：00 or before dawn. Air temperature near the soil surface （Ta） and soil temperature at 10 cm depth （Tlo） exerted dominant control on the diurnal variations of soil respiration. The time-windows 7：00-9：00 could be used as the optimal measuring time to represent the daily mean soil CO2 effiux at the Cv, Pd, Lc and Pa sites. The daily mean soil CO2 effiux was close to the soil COz effiux from 15：00 to 17：00 and the mean of 2 individual soil CO2 effiux from 15：00 to 19：00 at the As and Sg sites, respectively. During nocturnal hours, negative soil CO2 fluxes （CO2 downwards into the soil） were frequently observed at the As and Sg sites, the magnitude of the negative CO2 fluxes were 0.10-1.55 gmol/（m2.s） and 0.10-0.69 gmol/（m2.s）at the two sites. The results im- plied that alkaline soils could absorb CO2 under natural condition, which might have significant implications to the global carbon budget accounting.

Displacement Trends of Slow-moving Landslides: Classification and Forecasting

A framework is proposed to characterize and forecast the displacement trends of slow-moving landslides, defined as the reactivation stage of phenomena in rocks or fine-grained soils, with movements localized along one or several existing shear surfaces. The framework is developed based on a thorough analysis of the scientific literature and with reference to significant reported case studies for which a consistent dataset of continuous displacement measurements is available. Three distinct trends of movement are defined to characterize the kinematic behavior of the active stages of slow-moving landslides in a velocity-time plot: a linear trend-type I, which is appropriate for stationary phenomena; a convex shaped trend-type II, which is associated with rapid increases in pore water pressure due to rainfall, followed by a slow decrease in the groundwater level with time; and a concave shaped trend-type III, which denotes a non-stationary process related to the presence of new boundary conditions such as those associated with the development of a newly formed local slip surface that connects with the main existing slip surface. Within the proposed framework, a model is developed to forecast future displacements for active stages of trend-type II based on displacement measurements at the beginning of the stage. The proposed model is validated by application to two case studies.

Dynamic prediction of gas emission based on wavelet neural network toolbox

This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time intervals through training the WNN with even time-interval samples. The method builds successive new model with the width of sliding window remaining invariable so as to obtain a dynamic prediction method for gas emission quantity. Furthermore, the method performs prediction by a self-developed WNN toolbox. Experiments indicate that such a model can overcome the deficiencies of the traditional static prediction model and can fully make use of the feature extraction capability of wavelet base function to reflect the geological feature of gas emission quantity dynamically. The method is characterized by simplicity, flexibility, small data scale, fast convergence rate and high prediction precision. In addition, the method is also characterized by certainty and repeatability of the predicted results. The effectiveness of this method is confirmed by simulation results. Therefore, this method will exert practical significance on promoting the application of WNN.

Application of Geodetic Receivers to Timing and Time Transfer

Two methods for smoothing pseudorange observable by Carrier and Doppler are discussed. Then the procedure based on the RINEX observation files is tested using the Ashtech Z-XII3T geodetic receivers driven by a stable external frequency at UNSO. This paper proposes to adapt this procedure for the links between geodetic receivers, in order to take advantage of the P codes available on L 1 and L 2. This new procedure uses the 30-second RINEX observations files, the standard of the International GPS Service (IGS), and processes the ionosphere-free combination of the codes P 1 and P 2; the satellite positions are deduced from the IGS rapid orbits, available after two days.

FPGA-based High-precision Measurement Algorithm for the Ultrasonic Echo Time of Flight

Based on the evaluation of advantages and disadvantages of high-precision digital time interval measuring algorithms, and combined with the principle of the typical time-difference ultrasonic flow measurement, the requirements for the measurement of echo time of flight put forward by the ultrasonic flow measurement are analyzed. A new high-precision time interval measurement algorithm is presented, which combines the pulse counting method with the phase delay interpolation. The pulse counting method is used to ensure a large dynamic measuring range, and a double-edge triggering counter is designed to improve the accuracy and reduce the counting quantization error. The phase delay interpolation is used to reduce the quantization error of pulse counting for further improving the time measurement resolution. Test data show that the systexn for the measurement of the ultrasonic echo time of flight based on this algorithm and implemented on an Field Programmable Gate Army（FleA） needs a relatively short time for measurement, and has a measurement error of less than 105 ps.

Application of well log normalization in coalfield seismic inversion

During the process of coal prospecting and exploration, different measurement time, different logging instruments and series can lead to systematic errors in well logs. Accordingly, all logging curves need to be normalized in the mining area. By studying well-logging normalization methods, and focusing on the characteristics of the coalfield, the frequency histogram method was used in accordance with the condition of the Guqiao Coal Mine. In this way, the density and sonic velocity at marker bed in the non-key well were made to close to those in the key well, and were eventually equal. Well log normalization was completed when this method was applied to the entire logging curves. The results show that the scales of logging data were unified by normalizing coal logging curves, and the logging data were consistent with wave impedance inversion data. A satisfactory inversion effect was obtained.

Pattern recognition and prediction study of rock burst based on neural network

Many monitoring measures were used in the production field for predicting rockburst.However, predicting rock burst according to complicated observation data is alwaysa pressing problem in this research field.Though the critical value method gets extensiveapplication in practice, it stresses only on the superficial change of data and overlooks alot of features of rock burst and useful information that is concealed and hidden in the observationtime series.Pattern recognition extracts the feature value of time domain, frequencydomain and wavelet domain in observation time series to form Multi-Feature vectors,using Euclidean distance measure as the separable criterion between the same typeand different type to compress and transform feature vectors.It applies neural network asa tool to recognize the danger of rock burst, and uses feature vectors being compressedto carry out training and studying.It is proved by test samples that predicting precisionshould be prior to such traditional predicting methods as pattern recognition and critical indicatormethod.

Mixing time in stirred vessels: A review of experimental techniques

Mixing time is de fined as the time required for achieving a certain degree of homogeneity of injected tracer in a unit operation vessel. It has been used as a key parameter for assessing the performance of a mixing system. From an experimental standpoint, several techniques have been developed for measuring the mixing time. Based on the disturbances to fl ow, they can be classi fied into two groups: non-intrusive and intrusive. However, depending on the type of data generated, they can be also classi fied into direct measurements and indirect measurements(Eulerian and Lagrangian). Since the techniques available for measuring mixing times in an agitated tank do not provide the same information, its choice depends on several factors, namely: accuracy, reproducibility,suitability, cost, sampling speed, type of data, and processing time. A review of the experimental techniques reported in the literature in the last 50 years for the measurement of mixing time in stirred vessels under single and gas–liquid fl ow conditions with Newtonian and non-Newtonian fl uids in the laminar and turbulent regime is made, and a comparison between these techniques is also presented.

Chaotic phenomenon and the maximum predictable time scale of observation series of urban hourly water consumption

The chaotic characteristics and maximum predictable time scale of the observation series of hourly water consumption in Hangzhou were investigated using the advanced algorithm presented here is based on the conventional Wolf's algorithm for the largest Lyapunov exponent. For comparison, the largest Lyapunov exponents of water consumption series with one-hour and 24-hour intervals were calculated respectively. The results indicated that chaotic characteristics obviously exist in the hourly water consumption system; and that observation series with 24-hour interval have longer maximum predictable scale than hourly series. These findings could have significant practical application for better prediction of urban hourly water consumption.

Ambient noise during rough weather and cyclones in the shallow Bay of Bengal

This paper presents ambient noise analysis during rough weather, using time series measurements from an automated noise measurement system in the shallow southwest Bay of Bengal during October–November 2010. The period witnessed low-pressure events including depressions and cyclones, with JAL cyclone passing close to the measurement site. The time series noise level shows a shift in mid-October, after which deep depressions and cyclones formed, with an average increase of 5–10 dB in the lower band and 2–3 dB in the higher band of frequencies. Furthermore, correlation between noise level and wave height(data from wave rider buoy deployed at the site) for sea state scale 3 and above shows good correlation with an increase in noise level with increase in wave height, the effect being most pronounced at 0.5 kHz. The noise captured during JAL was analysed to identify the spectrum components due to convective precipitation and heavy wind/wave activity and shows anomalously high levels during the crossing of the cyclone. Rain noise spectra from the rain bands associated with the wall of the cyclone are reported. This has been correlated with radar refl ectivity measurements to ascertain the presence of rain, and discriminate between convective and stratiform types. Also, vertical directionality pattern of ambient noise during JAL showed clearly distinct surface contributions. On the whole, knowledge of ambient noise fields during high sea states and precipitation is useful in optimizing SONAR performance. The findings at the study site have been compared with measurements from other shallow water locations during rough weather.

A new process monitoring method based on noisy time structure independent component analysis

Conventional process monitoring method based on fast independent component analysis(Fast ICA) cannot take the ubiquitous measurement noises into account and may exhibit degraded monitoring performance under the adverse effects of the measurement noises. In this paper, a new process monitoring approach based on noisy time structure ICA(Noisy TSICA) is proposed to solve such problem. A Noisy TSICA algorithm which can consider the measurement noises explicitly is firstly developed to estimate the mixing matrix and extract the independent components(ICs). Subsequently, a monitoring statistic is built to detect process faults on the basis of the recursive kurtosis estimations of the dominant ICs. Lastly, a contribution plot for the monitoring statistic is constructed to identify the fault variables based on the sensitivity analysis. Simulation studies on the continuous stirred tank reactor system demonstrate that the proposed Noisy TSICA-based monitoring method outperforms the conventional Fast ICA-based monitoring method.

Spatio-temporal Difference and Influencing Factors of Environmental Adaptability Measurement of Human-sea Economic System in Liaoning Coastal Area

Adaptability theory is an important tool to analyze the degree, mechanism and process of interaction between human and environment, which provides a new perspective for the research of sustainability assessment. Based on the entropy weight-TOPSIS method and the panel Tobit model from the perspective of adaptability, spatio-temporal difference and influencing factors of environmental adaptability assessment of human-sea economic system in Liaoning coastal area was measured by using the city panel data from 2000 to 2014. The results indicate that: 1) The environmental adaptability of human-sea economic system in Liaoning coastal area rose slowly from 2000 to 2014, the developing trend of each city was linearly related, and Dalian was in a leading position. 2) The different adaptability elements and adaptability subsystem show polarization phenomenon and completely different regional evolution characteristics. The adaptability of human-sea environment system and human-sea economic system rose slowly and had the characteristics of linear relationship, and the adaptability of human-sea environment system is the main reason for the difference of environmental adaptability of human-sea economic system. 3) Science and technology, environmental management, marine economic development level, port construction are the driving factors of the healthy development of environmental adaptability of urban human-sea economic system.