Modified filter for mean elements estimation with state jumping

To investigate the real-time mean orbital elements(MOEs)estimation problem under the influence of state jumping caused by non-fatal spacecraft collision or protective orbit trans-fer,a modified augmented square-root unscented Kalman filter(MASUKF)is proposed.The MASUKF is composed of sigma points calculation,time update,modified state jumping detec-tion,and measurement update.Compared with the filters used in the existing literature on MOEs estimation,it has three main characteristics.Firstly,the state vector is augmented from six to nine by the added thrust acceleration terms,which makes the fil-ter additionally give the state-jumping-thrust-acceleration esti-mation.Secondly,the normalized innovation is used for state jumping detection to set detection threshold concisely and make the filter detect various state jumping with low latency.Thirdly,when sate jumping is detected,the covariance matrix inflation will be done,and then an extra time update process will be con-ducted at this time instance before measurement update.In this way,the relatively large estimation error at the detection moment can significantly decrease.Finally,typical simulations are per-formed to illustrated the effectiveness of the method.

Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.

Study on the estimation of Euler angles for Macao Science Satellite-1

The Euler angle estimation is a calibration method for vector data measured by the magnetometer on a satellite.It is used to find the relative rotation between the coordinate system of the magnetometer and the satellite(usually determined by Star Imagers).Before launch of the low-orbit,low-inclination Macao Science Satellite-1(known as MSS-1),we simulated the estimation of Euler angles by using the magnetic measurements of the in-orbit Swarm and China Seismo-Electromagnetic Satellite(noted as CSES),with various data combinations.In this study,11 data sets were designed to analyze the estimation results for the MSS-1 orbit by using a joint estimation method of the geomagnetic field model parameters and Euler angles.For the model results,we found that all the spatial power spectral lines showed behavior consistent with that of the CHAOS-7.8 model at low degrees(corresponding to large-scale magnetic signals).The spectra of models without global data coverage deviated much more(by a maximum of~10^(4) nT^(2))from those of the CHAOS-7.8 model at higher degrees.For models with global data coverage and with various data combinations,the spectral lines were distributed similarly.Moreover,the models with accordant power spectral distributions demonstrated different Euler angle estimations.As more vector data at higher latitudes were included,the estimated Euler angles varied monotonically in all three directions.The models with vector data in the same latitude range showed similar Euler angle results,regardless of whether the poleward scalar data were included.The largest value difference was found between the models using vector data within±40°latitudes and those using vector data within±60°latitudes,which reached to~28″.Therefore,we concluded that the inversion of the spherical harmonic Gauss coefficients in our tests was mainly affected by the spatial coverage range of the data,whereas the estimation of Euler angles largely depended on the latitude range where the vector data could be obtained.These results can be used for future in-flight data testing.We expect the estimation of Euler angles to improve as other methods are adopted.

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried out.This has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the day-aheadmarket.The standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique.The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub limitations.Additionally,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

Estimation of S-wave Velocity for Gas Hydrate Reservoir in the Shenhu Area,North South China Sea

Estimation of S-wave velocity using logging data has mainly been performed for sandstone,mudstone and oil and gas strata,while its application to hydrate reservoirs has been largely overlooked.In this paper we present petrophysical methods to estimate the S-wave velocity of hydrate reservoirs with the P-wave velocity and the density as constraints.The three models used in this paper are an equivalent model(MBGL),a three-phase model(TPBE),and a thermo-elasticity model(TEM).The MBGL model can effectively describe the internal relationship among the components of the rock,and the estimated P-wave velocities are in good agreement with the measured data(2.8% error).However,in the TPBE model,the solid,liquid and gas phases are considered to be independent of each other,and the estimation results are relatively low(46.6% error).The TEM model is based on the sensitivity of the gas hydrate to temperature and pressure,and the accuracy of the estimation results is also high(3.6% error).Before the estimation,the occurrence patterns of hydrates in the Shenhu area were examined,and occurrence state one(the hydrate is in solid form in the reservoir) was selected for analysis.By using the known P-wave velocity and density as constraints,a reasonable S-wave velocity value(ranging from 400 to 1100 m s^(-1) and for a hydrate layer of 1100 m s^(-1)) can be obtained through multiple iterations.These methods and results provide new data and technical support for further research on hydrates and other geological features in the Shenhu area.

Comparison of Linearized Kalman Filter and Extended Kalman Filter for Satellite Motion States Estimation

The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but it should not be used for estimating the state of a nonlinear system such as a satellite motion because it is difficult to obtain the desired estimation results.The linearized Kalman filtering approach and the extended Kalman filtering approach have been proposed for a general nonlinear system.The equations of satellite motion are described.The satellite motion states are estimated,and the relevant estimation errors are calculated through the estimation algorithms of the both above mentioned approaches implemented in Matlab are estimated.The performances of the extended Kalman filter and the linearized Kalman filter are compared.The simulation results show that the extended Kalman filter is much better than the linearized Kalman filter at the aspect of estimation effect.

A Model of Federated Evidence Fusion for Real-time Urban Traffic State Estimation

In order to make full use of heterogeneous multi-sensor data to serve urban intelligent transportation systems, a real-time urban traffic state fusion model was proposed, named federated evidence fusion model. The model improves conventional D-S evidence theory in temporal domain, such that it can satisfy the requirement of real-time processing and utilize traffic detection information more efficaciously. The model frame and computational procedures are given. In addition, a generalized reliability weight matrix of evidence is also presented to increase the accuracy of estimation. After that, a simulation test is presented to explain the advantage of the proposed method in comparison with conventional D-S evidence theory. Besides, the validity of the model is proven by the use of the data of loop detectors and GPS probe vehicles collected from an urban link in Shanghai. Results of the experiment show that the proposed approach can well embody and track traffic state at character level in real-time conditions.

Crosstalk Model and Estimation Formula for VLSI Interconnect Wires

We develop an interconnect crosstalk estimation model on the assumption of linearity for CMOS device. First, we analyze the terminal response of RC model on the worst condition from theS field to the time domain. The exact 3 order coefficients inS field are obtained due to the interconnect tree model. Based on this, a crosstalk peak estimation formula is presented. Unlike other crosstalk equations in the literature, this formula is only used coupled capacitance and grand capacitance as parameter. Experimental results show that, compared with the SPICE results, the estimation formulae are simple and accurate. So the model is expected to be used in such fields as layout-driven logic and high level synthesis, performance-driven floorplanning and interconnect planning.

Time Delay Estimation Based on Entropy Estimation

This paper presents a novel time delay estimation （TDE） method using the concept of entropy. The relative delay is estimated by minimizing the estimated joint entropy of multiple sensor output signals. When estimating the entropy, the information about the prior distribution of the source signal is not required. Instead, the Parzen window estimator is employed to estimate the density function of the source signal from multiple sensor output signals. Meanwhile, based on the Parzen window estimator, the Renyi＇s quadratic entropy （RQE） is incorporated to effectively and efficiently estimate the high-dimensional joint entropy of the multichannel outputs. Furthermore, a modified form of the joint entropy for embedding information about reverberation （multipath reflections） for speech signals is introduced to enhance the estimator＇s robustness against reverberation.

ESTIMATION OF THEORETICAL POTENTIAL AND EXPLOITABLE QUANTITY OF CHINA'S OCEANIC THERMAL ENERGY

Two estimaton methods are used to calculate the theoretical reservoir potential of China's oceanic thermal energy. One is based on the measured temperature difference between the surface water and the deep water, the other on the net radiation energy income from solar insolation either measured or deduced. The results from these two methods are compared and examined. Then, the maximum amount of the exploitable thermal energy is calculated based on the assumption of a Carnot cycle efficiency. In the process of estimation, such factors as water depth, seasonal water temperature variation and geographic location have been taken into account.The theoretical reservoir capacity and the exploitable quantity of the thermal energy of China's four seas are thus estimated separately.

Quasi-Negative Binomial: Properties, Parametric Estimation, Regression Model and Application to RNA-SEQ Data

Background: The Poisson and the Negative Binomial distributions are commonly used to model count data. The Poisson is characterized by the equality of mean and variance whereas the Negative Binomial has a variance larger than the mean and therefore both models are appropriate to model over-dispersed count data. Objectives: A new two-parameter probability distribution called the Quasi-Negative Binomial Distribution (QNBD) is being studied in this paper, generalizing the well-known negative binomial distribution. This model turns out to be quite flexible for analyzing count data. Our main objectives are to estimate the parameters of the proposed distribution and to discuss its applicability to genetics data. As an application, we demonstrate that the QNBD regression representation is utilized to model genomics data sets. Results: The new distribution is shown to provide a good fit with respect to the “Akaike Information Criterion”, AIC, considered a measure of model goodness of fit. The proposed distribution may serve as a viable alternative to other distributions available in the literature for modeling count data exhibiting overdispersion, arising in various fields of scientific investigation such as genomics and biomedicine.

The Global Attractors and Dimensions Estimation for the Higher-Order Nonlinear Kirchhoff-Type Equation with Strong Damping

The initial boundary value problems for a class of high order Kirchhoff type equations with nonlinear strongly damped terms are considered. We establish the existence and uniqueness of the global solution of the problem by using prior estimates and Galerkin’s method under proper assumptions for the rigid term. Then the compact method is used to prove the existence of a compact family of global attractors in the solution semigroup generated by the problem. Finally, the Frechet differentiability of the operator semigroup and the decay of the volume element of linearization problem are proved, and the Hausdorff dimension and Fractal dimension of the family of global attractors are obtained.

Estimation and Forecasting Survival of Diabetic CABG Patients (Kalman Filter Smoothing Approach)

In this paper, we present a new approach (Kalman Filter Smoothing) to estimate and forecast survival of Diabetic and Non Diabetic Coronary Artery Bypass Graft Surgery (CABG) patients. Survival proportions of the patients are obtained from a lifetime representing parametric model (Weibull distribution with Kalman Filter approach). Moreover, an approach of complete population (CP) from its incomplete population (IP) of the patients with 12 years observations/follow-up is used for their survival analysis [1]. The survival proportions of the CP obtained from Kaplan Meier method are used as observed values yt?at time t (input) for Kalman Filter Smoothing process to update time varying parameters. In case of CP, the term representing censored observations may be dropped from likelihood function of the distribution. Maximum likelihood method, in-conjunction with Davidon-Fletcher-Powell (DFP) optimization method [2] and Cubic Interpolation method is used in estimation of the survivor’s proportions. The estimated and forecasted survival proportions of CP of the Diabetic and Non Diabetic CABG patients from the Kalman Filter Smoothing approach are presented in terms of statistics, survival curves, discussion and conclusion.

Model Predictive Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) with Online Parameter Estimation Based on Extended Kalman Filter

Aiming at the torque and flux ripples in the direct torque control and the time-varying parameters for permanent magnet synchronous motor (PMSM), a model predictive direct torque control with online parameter estimation based on the extended Kalman filter for PMSM is designed. By predicting the errors of torque and flux based on the model and the current states of the system, the optimal voltage vector is selected to minimize the error of torque and flux. The stator resistance and inductance are estimated online via EKF to reduce the effect of model error and the current estimation can reduce the error caused by measurement noise. The stability of the EKF is proved in theory. The simulation experiment results show the method can estimate the motor parameters, reduce the torque, and flux ripples and improve the performance of direct torque control for permanent magnet synchronous motor (PMSM).

A Rapid Estimation Method of Structural Fatigue Analysis for a 17k Ton DWT Oil Tanker

疲劳裂缝和疲劳损坏是为轮船的重要的期并且近海结构很长时间。在最后十年，与在壳结构和逐渐地大的轮船尺寸的更高张力的钢的介绍，然而，更大的注意应该被给予使问题疲劳。的大多数研究焦点更容易存取轮船的疲劳力量。另外，主要分类社会已经释放了他们的疲劳评价笔记。由于影响疲劳表演的因素的复杂性，然而从货物，不同压力部件的联合，本地结构细节的集中上的压力，工具压力，和腐蚀剂环境装载例如波浪并且迫使，有有改变分类社会的不同说明，从不同疲劳评价方法导致不同结果。这篇论文证实 Det Norske Veritas (DNV ) 分类笔记使对解释疲劳评价的过程的轮船结构的评价疲劳并且简化了方法。最后，疲劳分析被一艘真实轮船的使用数据执行，结果的可靠性被估计。

一种基于μ-S模型的最佳滑移率辨识估计器设计

为了使基于滑移率识别的汽车防抱死控制器实现最优控制,在Kiencke μ-S模型的基础上,利用改进遗忘因子递推最小二乘算法设计了最佳滑移率辨识估计器,并将辨识估计器的最佳滑移率和峰值附着系数估算结果与Burckhardt μ-S模型下的结果进行了对比.将辨识估计器应用于汽车防抱死制动系统的模糊滑模控制器中,在单一路面和跃变路面条件下进行仿真实验.实验结果表明,辨识估计器的误差小、延迟小,基于最佳滑移率识别的防抱死控制器能实现最佳滑移率的在线辨识和快速追踪,有效提升制动效能.

LSFP下的机器人视觉定位技术研究

针对当前点云的定位算法中,多平面分割效果差、误匹配以及定位精度不够高等问题,提出LSFP的定位思想和C-S分割算法,对目标物体进行定位。在深度相机场景下,利用点云处理算法初步获取目标的位姿,经手眼标定后,进行初步引导;再使用3D扫描仪进一步定位目标物体。结果表明:(1)C-S分割算法对多平面分割效果良好,能更准确地去除多余平面,减少点云数量。(2)在垂直于Z轴且Z轴坐标值为171 mm和-10 mm的平面上,仅PrimeSense的定位距离的均方根误差为7.3 mm和8.2 mm,LSFP下的定位距离的均方根误差为2.6 mm和3.2 mm。(3)LSFP定位思想能扩大场景定位的范围,提高物体的定位精度,具有良好的准确性。

AN INTEGRAL ESTIMATE AND THE EQUIVALENT NORMS ON F(p, q, s, k) SPACES IN THE UNIT BALL

In this article, the authors give a typical integral＇s bidirectional estimates for allcases. At the same time, several equivalent characterizations on the F（p, q, s, k） space in theunit ball of Cn are given.

EXPLICIT ERROR ESTIMATE FOR THE NONCONFORMING WILSON'S ELEMENT

In this article, we study the explicit expressions of the constants in the error estimate of the nonconforming finite element method. We explicitly obtain the approximation error estimate and the consistency error estimate for the Wilson＇s element without the regular assumption, respectively, which implies the final finite element error estimate. Such explicit a priori error estimates can be used as computable error bounds.

Sharp estimates for Hübner’s upper bound function with applications

New better estimates, which are given in terms of elementary functions, for the function r →（2/π）（1 -r2）κ（r）κ′（r） ＋ logr appearing in Hubner＇s sharp upper bound for the Hersch-Pfluger distortion function are obtained. With these estimates, some known bounds for the Hersch-Pfluger distortion function in quasiconformal theory are improved, thus. improving the explicit quasiconformal Schwarz lemma and some known estimates for the solutions to the Ramanujan modular equations.