Multiple Kalman filters model with shaping filter GPS real-time deformation analysis

In order to detect the deformation in real-time of the GPS time series and improve its reliability, the multiple Kalman filters model with shaping filter was proposed. Two problems were solved: firstly, because the GPS real-time deformation series with a high sampling rate contain coloured noise, the multiple Kalman filter model requires the white noise, and the multiple Kalman filters model is augmented by a shaping filter in order to reduce the colored noise; secondly, the multiple Kalman filters model with shaping filter can detect the deformation epoch in real-time and improve the quality of GPS measurements for the real-time deformation applications. Based on the comparisons of the applications in different GPS time series with different models, the advantages of the proposed model were illustrated. The proposed model can reduce the colored noise, detect the smaller changes, and improve the precision of the detected deformation epoch.

Kalman Fliter Approach to Multisensor Registration of Moving Platform

Aim To find an effective method to remove the registration error in multi-sensor systems. Methods A Kalman filtering technique was proposed to estimate and remove sensor bias and sensor fare tilt errors in multisensor systems with a moving platform. Results Simulation results are presented to demonstrate the performance of the approach. Conclusion The Kalman filter algorithm am detect registration errors and use this information to converge tracks from independent sensors. This is particularly important if the data from the sensors are to fused.

Sensor Registration in Asynchronous Data Fusion

To find an effective method to estimate and remove the registration error in asynchronous multisensor system, Kalman filtering technique and least squares approach have been proposed to estimate and remove sensor bias and sensor frame tilt errors in multisensor systems with asynchronous data. Simulation results is presented to demonstrate the performance of these approaches. The least squares approach can compress measurements to any time. The Kalman filter algorithm can detect registration errors and use the information to converge tracks from independent sensors. This is particularly important if the data from the sensors are to be fused.

《黑色竞技场》的社会意义

《黑色竞技场》(The Black Arena)是美国畅销书《教父》(The Godfather)、《傻瓜该死》(Fools Die)和《西西里人》(The Sicilian)的作者马里奥·普佐(Mario Puzo)的处女作,1953年由美国纽约德尔出版公司(Dell Inco)初版,1955年再版。全书250页,分25章,其中第18章曾由美国德尔出版公司在《美国先锋》杂志上,以《恋爱中的埃迪·卡辛》为题刊出过。

值得重视的公共关系学

当今世界是无处不存在“关系”的世界。任何组织的发展都有赖于公共要求的满足和舆论的支持。利用好公共关系,就可扩大企业的影响,提高在竞争中的地位,这一观念已普遍为人们所接受。现代公共关系事业,起源于19世纪末、20世纪初的美国。早在1882年。

《科学》杂志把黑洞的发现评为2019年度科学突破

视界望远镜(the Event Horizon Telescope)在2019年春天拍摄到一张超大质量黑洞的照片,并揭示了在已知宇宙中最黑和最难以解释的现象,《科学》杂志称其为“2019年度科学突破”。这个重大发现是200多位科学家共同努力的结果。2019年4月10日,当黑洞的图像宣布后,世界对此事的热烈反应程度也令视界望远镜的项目负责人之一,天文学家舍普·多尔曼(Shep Doeleman)大为吃惊。他说:“看到黑洞的照片刊登在所有报纸的头版,我意识到其影响已远超我们的团队和科学家的想象。我们组成的国际团队把地球变成一个望远镜,捕捉到宇宙中最神秘的物体图像,人们惊叹于通过团队合作可以做出如此伟大的事情。”

Target Tracking Using the Interactive Multiple Model Method

Aim To develop a practical target tracking algorithm for different motion modes. Methods After creation of the new model, it was implemented by computer simulation to prove its performance and compared with the often-used current statistical model. Results The simulation results show that the new IMM (interactive multiple model) have low tracking error in both maneuVering segment and non^Inaneuwi segment while the current statistical model bas muCh higher tracking error in non-maneuvering segment. Conclusion In the point of trackintaccuracy, the new IMM method is much better than the current acceleration method. It can develop into a practical target hacking method.

Maneuvering target tracking using threshold interacting multiple model algorithm

To avoid missing track caused by the target maneuvers in automatic target tracking system, a new maneuvering target tracking technique called threshold interacting multiple model （TIMM） is proposed. This algorithm is based on the interacting multiple model （IMM） method and applies a threshold controller to improve tracking accuracy. It is also applicable to other advanced algorithms of IMM. In this research, we also compare the position and velocity root mean square （RMS） errors of TIMM and IMM algorithms with two different examples. Simulation results show that the TIMM algorithm is superior to the traditional IMM alzorithm in estimation accuracy.

Multi-sensor federated unscented Kalman filtering algorithm in intermittent observations

Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Firstly, combined with the residual detection strategy, effective observations are cor- rectly identified. Secondly, according to the missing characteristic of observations and the structural feature of unscented Kalman filter, the iterative process of the single-sensor unscented Kalman filter in intermittent observations is given. The key idea is that the state estimation and its error covariance matrix are replaced by the state one-step prediction and its error covariance matrix, when the phe- nomenon of observations missing occurs. Finally, based on the realization mechanism of federated filter, a new fusion framework of state estimation from each local node is designed. And the filtering precision of system state is improved further by the effective management of observations missing and the rational utilization of redundancy and complementary information among multi-sensor observa- tions. The theory analysis and simulation results show the feasibility and effectiveness of the pro- posed algorithm.

An improved method for multiple targets tracking

The difficulty of multiple targets tracking is how to quickly fulfill the target matching from one flame image to another and fix the position of the target. In order to accurately choose target feature information for reliable matching, simplify operations under the reliable precondition, and realize precise moving objects tracking, an approach based on Kalman prediction and feature matching was proposed. The position of the target in next frame image was predicted by Kalman, and then the moving objects of two adjacent frames were matched by the centroid and area methods. When occlusion occurs, the best matching result was found to realize tracking by matching matrix algorithm. The simulation results show that the proposed method can achieve multiple targets tracking accurately and in real-time under complicated motion movements.

Application of interacting multi-model algorithm in gyro signal processing

There is one problem existing in gyroscope signal processing,which is that single models can＇ t adapt to change of carrier maneuvering process.Since it is difficult to identify the angular motion state of gyroscope carriers,interacting multiple model （IMM） is employed here to solve the problem.The Kalman filter-based IMM （IMMKF） algorithm is explained in detail and its application in gyro signal processing is introduced.And with the help of the Singer model,the system model set of gyro outputs is constructed.In order to demonstrate the effectiveness of the proposed approach,static experiment and dynamic experiment are carried out respectively.Simulation analysis results indicate that the IMMKF algorithm is excellent in eliminating gyro drift errors,which could adapt to the change of carrier maneuvering process well.

Multi-sensor Hybrid Fusion Algorithm Based on Adaptive Square-root Cubature Kalman Filter

In the normal operation condition, a conventional square-root cubature Kalman filter （SRCKF） gives sufficiently good estimation results. However, if the measurements are not reliable, the SRCKF may give inaccurate results and diverges by time. This study introduces an adaptive SRCKF algorithm with the filter gain correction for the case of measurement malfunctions. By proposing a switching criterion, an optimal filter is selected from the adaptive and conventional SRCKF according to the measurement quality. A subsystem soft fault detection algorithm is built with the filter residual. Utilizing a clear subsystem fault coefficient, the faulty subsystem is isolated as a result of the system reconstruction. In order to improve the performance of the multi-sensor system, a hybrid fusion algorithm is presented based on the adaptive SRCKF. The state and error covariance matrix are also predicted by the priori fusion estimates, and are updated by the predicted and estimated information of subsystems. The proposed algorithms were applied to the vessel dynamic positioning system simulation. They were compared with normal SRCKF and local estimation weighted fusion algorithm. The simulation results show that the presented adaptive SRCKF improves the robustness of subsystem filtering, and the hybrid fusion algorithm has the better performance. The simulation verifies the effectiveness of the proposed algorithms.

Application of interacting multiple model in integrated positioning system of vehicle

To solve low precision and poor stability of the extended Kalman filter （EKF） in the vehicle integrated positioning system owing to acceleration, deceleration and turning （hereinafter referred to as maneuvering） , the paper presents an adaptive filter algorithm that combines interacting multiple model （IMM） and non linear Kalman filter. The algorithm describes the motion mode of vehicle by using three state spacemode]s. At first, the parallel filter of each model is realized by using multiple nonlinear filters. Then the weight integration of filtering result is carried out by using the model matching likelihood function so as to get the system positioning information. The method has advantages of nonlinear system filter and overcomes disadvantages of single model of filtering algorithm that has poor effects on positioning the maneuvering target. At last, the paper uses IMM and EKF methods to simulate the global positioning system （OPS）/inertial navigation system （INS）/dead reckoning （DR） integrated positioning system, respectively. The results indicate that the IMM algorithm is obviously superior to EKF filter used in the integrated positioning system at present. Moreover, it can greatly enhance the stability and positioning precision of integrated positioning system.

Blind Channel Equalization Algorithm Based on Dual Unscented Kalman Filter for Chaotic Multi-Input Multi-Output Communication Systems

To reduce channel noise,fading,and inter-user interference effectively in the chaotic communication systems with multi-user,a blind channel equalization algorithm based on dual unscented Kalman filter algorithm is proposed.Assuming that the coefficients of a multi-input multi-output (MIMO) channel can be described by an autoregressive model,two separate state-space representations are used for the signals and coefficients.Then two unscented Kalman filters are used to estimate chaotic signals and channel coefficients simultaneously.The simulation results indicate that the algorithm can effectively track the coefficients of the multi-path fading channel in chaotic MIMO communication systems at a fast convergence speed.

Journal of Intelligent Agricultural Mechanization Visual navigation in orchard based on multiple images at different shooting angles

The orchards usually have rough terrain,dense tree canopy and weeds.It is hard to use GNSS for autonomous navigation in orchard due to signal occlusion,multipath effect,and radio frequency interference.To achieve autonomous navigation in orchard,a visual navigation method based on multiple images at different shooting angles is proposed in this paper.A dynamic image capturing device is designed for camera installation and multiple images can be shot at different angles.Firstly,the obtained orchard images are classified into sky and soil detection stage.Each image is transformed to HSV space and initially segmented into sky,canopy and soil regions by median filtering and morphological processing.Secondly,the sky and soil regions are extracted by the maximum connected region algorithm,and the region edges are detected and filtered by the Canny operator.Thirdly,the navigation line in the current frame is extracted by fitting the region coordinate points.Then the dynamic weighted filtering algorithm is used to extract the navigation line for the soil and sky detection stage,respectively,and the navigation line for the sky detection stage is mirrored to the soil region.Finally,the Kalman filter algorithm is used to fuse and extract the final navigation path.The test results on 200 images show that the accuracy of visual navigation path fitting is 95.5%,and single frame image processing costs 60 ms,which meets the real-time and robustness requirements of navigation.The visual navigation experiments in Camellia oleifera orchard show that when the driving speed is 0.6 m/s,the maximum tracking offset of visual navigation in weed-free and weedy environments is 0.14 m and 0.24 m,respectively,and the RMSE is 30 mm and 55 mm,respectively.

丈夫们的聚会

一次神秘的抽奖,会给获胜者带来意想不到的奖励……1房间里灯光昏暗,以至于我几乎辨认不出和我同在这个房间内的人都有谁。我有点生气,小心翼翼地穿行到房间中心堆放了座椅的地方。空气里充斥了香烟的烟雾,浓得像我妻子的香水一样,也差不多一样让人窒息。我拖出一把金属折叠椅,坐到一名不认识的男子旁边,眯起眼睛,打量房间里的每一张面孔。没一张面孔看着脸熟。

“借警自杀”的成因与应对

假警察之手的自杀现象是指某些人想结束自己的生命但又不打算杀死自己,于是把自己放在警察的对立面,促使警察'被迫'杀死他,这种现象俗称'借警自杀'(suicide by cop),也称蓝色自杀(blue suicide),因为在英语中,蓝色表示沮丧、忧郁的意思。

1993年2月经审查同意选购进口影片7部

《无敌悍将》前战斗机飞行员泰勒被黑社会陷害无辜入狱,与黑帮毒枭汤尼金同在一间牢房,双方引发仇恨的火花。汤尼金指使手下谋杀了泰勒的妹妹,泰勒忍无可忍,只好以自己的方式去讨回公道。编剧:莫斯赫·哈德导演:约翰·斯图尔特香港影片,长10本。

国际资讯

17000年前巨石阵因干旱重现据路透社近日报道,伴随着非洲气团自5月涌入伊比利亚半岛,西班牙全国经历了有史以来最热的夏天,部分地区持续超过40℃,但同时带来了一个意想不到的结果——多尔曼巨石阵重见天日。多尔曼巨石阵被称为西班牙巨石阵,由数十块巨石组成。该巨石阵的历史可以追溯到公元前5000年,由德国考古学家雨果·奥伯迈尔于1926年发现,但巨石阵在1963年因当地建水库而被淹没。

全球科技热点

西班牙今年夏季西班牙遭遇了严重干旱。这也使一个自1963年以来一直被淹没在人造水库中的椭圆巨石阵浮出水面。这个巨石阵被称为瓜达拉帕拉的多尔曼(Dolmen of Guadalperal) 有超过4000年历史,其中至少有100块立石。