Anti-Jamming Algorithm Based on Spatial Blind Search for Global Navigation Satellite System Receiver

A novel subspace projection anti-jamming algorithm based on spatial blind search is proposed,which uses multiple single-constrained subspace projection parallel filters.If the direction of arrival(DOA)of a satellite signal is unknown,the traditional subspace projection anti-jamming algorithm cannot form the correct beam pointing.To overcome the problem of the traditional subspace projection algorithm,multiple single-constrained subspace projection parallel filters are used.Every single-constrained anti-jamming subspace projection algorithm obtains the optimal weight vector by searching the DOA of the satellite signal and uses the output of cross correlation as a decision criterion.Test results show that the algorithm can suppress the jamming effectively,and generate high gain toward the desired signal.The research provides a new idea for the engineering implementation of a multi-beam anti-jamming algorithm based on subspace projection.

Usage of global navigation systems for detection of dangerous meteorological phenomena

The method of dangerous meteorological phenomenon detection using the data of coordinate measurement by receivers of global navigation satellite system （GLONASS） and global positioning system （GPS） is proposed. The possibility of thunderstorm courses and strong clouds detection on data of pseudo-distances and altitudes is shown theoretically and confirmed experimentally.

Evaluation of global navigation satellite system spoofing efficacy

The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.

Compact and broadband circularly polarized ring antenna with wide beam-width for multiple global navigation satellite systems

A compact and broadband circularly polarized （CP） annular ring antenna with wide beam-width is proposed for multiple global navigation satellite systems （GNSS） in the L1 band. The annular ring is excited by two modified L-probes with quadrature phase difference. It has a 36.3% 10-dB return loss bandwidth and a 13% 3-dB axial ratio bandwidth, because of the orthogonal L-probes with 90° phase difference. The measured peak gain of the antenna is 3.9 dBic. It can detect the satellites at lower elevation as its half power beam-width （HPBW） is 113° in both the x-z and y-z planes, achieving a cross-polarization level of larger than 25 dB. Noticeably, the antenna achieves 89% size reduction compared with the conventional half wavelength patch antennas. It can be used in hand-held navigation devices of multiple GNSS such as COMPASS, Galileo, GPS and GLONASS.

The Performance Evaluation of the Integration of Inertial Navigation System and Global Navigation Satellite System with Analytic Constraints

The integration of GNSS （Global Navigation Satellite System） and INS （Inertial Navigation System） using IMU （Inertial Measurement Unit） is now widely used for MMS （Mobile Mapping System） and navigation applications to seamlessly determine position, velocity and attitude of the mobile platform. With low cost, small size, ligh weight and low power consumtion, the MEMS （Micro-Electro-Mechanical System） IMU and low cost GPS （Global Positioning System） receivers are now the trend in research and using for many applications. However, researchs in the literature indicated that the the performance of the low cost INS/GPS systems is still poor, particularly, in case of GNSS-noise environment. To overcome this problem, this research applies analytic contrains including non-holonomic constraint and zero velocity update in the data fusion engine such as Extended Kalman Filter to improve the performance of the system. The benefit of the proposed method will be demonstrated through experiments and data analysis.

SINS/CNS/GPS integrated navigation algorithm based on UKF

A new nonlinear algorithm is proposed for strapdown inertial navigation system （SINS）/celestial navigation system （CNS）/global positioning system （GPS） integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter （UKF） to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle＇s attitude and has less variables than the quaternion. Also, the UKF method is simplified to estimate the system error model, which can both lead to less calculation and reduce algorithm implement time. In the information fusion section, a modified federated Kalman filter is proposed to solve the singular covariance problem. Specifically, the new algorithm is applied to maneuvering vehicles, and simulation results show that this algorithm is more accurate than the linear integrated navigation algorithm.

IAE-adaptive Kalman filter for INS/GPS integrated navigation system

A marine INS/GPS adaptive navigation system is presented. GPS with two antenna providing vessel＇ s altitude is selected as the auxiliary system fusing with INS to improve the performance of the hybrid system. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The standard Kalman filter （SKF） assumes that the statistics of the noise on each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce fuzzy logic control method into innovation-based adaptive estimation adaptive Kalman filtering （IAE-AKF） algorithm, and accordingly propose various adaptive Kalman filters. However how to design the fuzzy logic controller is a very complicated problem still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAEAKF algorithm theoretically in detail, the approach is tested by the simulation based on the system error model of the developed INS/GPS integrated marine navigation system. Simulation results show that the adaptive Kalman filter outperforms the SKF with higher accuracy, robustness and less computation. It is demonstra- ted that this proposed approach is a valid solution for the unknown changing measurement noise exited in the Kalman filter.

An INS/GNSS integrated navigation in GNSS denied environment using recurrent neural network

In view of the failure of GNSS signals,this paper proposes an INS/GNSS integrated navigation method based on the recurrent neural network(RNN).This proposed method utilizes the calculation principle of INS and the memory function of the RNN to estimate the errors of the INS,thereby obtaining a continuous,reliable and high-precision navigation solution.The performance of the proposed method is firstly demonstrated using an INS/GNSS simulation environment.Subsequently,an experimental test on boat is also conducted to validate the performance of the method.The results show a promising application prospect for RNN in the field of positioning for INS/GNSS integrated navigation in the absence of GNSS signal,as it outperforms extreme learning machine(ELM)and EKF by approximately 30%and 60%,respectively.

GPS/VISNAV integrated relative navigation and attitude determination system for ultra-close spacecraft formation flying

For the improvement of accuracy and better fault-tolerant performance, a global position system （GPS）/vision navigation （VISNAV） integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying. Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design. Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.

Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.

Global Inverse Optimal Tracking Control of Underactuated Omni-directional Intelligent Navigators （ODINs）

This paper presents a design of optimal controllers with respect to a meaningful cost function to force an underactuated omni-directional intelligent navigator （ODIN） under unknown constant environmental loads to track a reference trajectory in two-dimensional space. Motivated by the vehicle＇s steering practice, the yaw angle regarded as a virtual control plus the surge thrust force are used to force the position of the vehicle to globally track its reference trajectory. The control design is based on several recent results developed for inverse optimal control and stability analysis of nonlinear systems, a new design of bounded disturbance observers, and backstepping and Lyapunov＇s direct methods. Both state- and output-feedback control designs are addressed. Simulations are included to illustrate the effectiveness of the proposed results.

GNSS autonomous navigation method for HEO spacecraft

For global navigation satellite system(GNSS)in the application of high earth orbit(HEO)determination,there are problems such as small number of visible satellites and weak signal magnitude.The transmitting and receiving errors of GNSS signal in the environment of HEO space are analyzed,and related compensating scheme is also proposed.Acquisition of GNSS signal is implemented by using weak signal acquisition technology based on Duffing.Precise tracking of weak GNSS signal is also realized by adopting dynamic detection and compensation technology based on Duffing chaotic oscillator.Simulation results show that,certain acquisition sensitivity and navigation precision can be reached,and the acquisition and tracking of weak GNSS signal can be realized by using the proposed technology,which provides good technology support for autonomous navigation of HEO and large elliptical spacecrafts.

LNA Design for Future S Band Satellite Navigation and 4G LTE Applications

A good design of LNA for S band satellite navigation receivers and 4G LTE wireless communication system has been implemented in this paper.Due to increased congestion in the present L band,the S Band frequency from 2483.5-2500 MHz has been allocated for the future satellite navigation systems.For this purpose ATF-34143 amplifier(pHEMT)having high electron mobility and fast switching response has been chosen due to its very low Noise Figure(NF).The amplifier has been designed having bandwidth of 0.8 GHz from 1.8-2.6 GHz.Because of the large bandwidth,the amplifier could serve many wireless communication applications including 4G LTE mobile communication at 2.1 GHz.The design was implemented using the micro strip technology offering extremely low noise figure of 0.312 dB and 0.377 dB for 2.1 GHz and 2.49 GHz respectively.The gain of the amplifier was low and found to be 10.281 dB and 9.175 dB.For the purpose of increasing the gain of an amplifier,the proposed LNA design was then optimized by using Wilkinson Power Divider(WPD).The Balanced LNA design using WPD offered very low noise figure of 0.422 dB and 0.532 dB respectively and the gain was considerably increased and was found to be 20.087 dB and 17.832 dB respectively against 2.1 GHz and 2.49 GHz.Simulations and measurements were taken in Agilent Advanced Design System(ADS)software.The suggested LNA can be used for a variety of wireless communications applications including the future S band satellite navigation systems.

Navigation and Control of the PRISMA Formation： In-Orbit Experience

This paper presents flight results and lessons learned from the Spaceborne Autonomous Formation Flying Experiment （SAFE） conducted by the German Space Operations Center in the frame of the Swedish PRISMA technology demonstration mission. PR1SMA involves two fully autonomous formation-flying spacecraft which have been launched in June 2010 in a dawn/dusk orbit at an altitude of 750 km. SAFE represents one of the first demonstrations in low Earth orbit of an advanced guidance, navigation and control system for dual-spacecraft formations. Innovative techniques based on carrier-phase differential GPS （Global Positioning System）, relative eccentricity/inclination vectors and impulsive maneuvering are validated and tuned in orbit to achieve centimeter accurate real-time relative navigation, reliable formation keeping at the meter level and flexible formation reconfiguration capabilities. The technologies demonstrated within SAFE are considered as key precursors of future distributed satellite systems for unrivaled remote sensing and space exploration.

Scene image recognition with knowledge transfer for drone navigation

In this paper,we study scene image recognition with knowledge transfer for drone navigation.We divide navigation scenes into three macro-classes,namely outdoor special scenes(OSSs),the space from indoors to outdoors or from outdoors to indoors transitional scenes(TSs),and others.However,there are difficulties in how to recognize the TSs,to this end,we employ deep convolutional neural network(CNN)based on knowledge transfer,techniques for image augmentation,and fine tuning to solve the issue.Moreover,there is still a novelty detection prob-lem in the classifier,and we use global navigation satellite sys-tems(GNSS)to solve it in the prediction stage.Experiment results show our method,with a pre-trained model and fine tun-ing,can achieve 91.3196%top-1 accuracy on Scenes21 dataset,paving the way for drones to learn to understand the scenes around them autonomously.

An Integrated Air Data / GPS Navigation System for Helicopters

In this study, the integration of two navigation systems Air Data System (ADS) and Global Positioning System (GPS) was aimed. ADS is a widely used navigation system which measures static and total air pressure and the air temperature. ADS has high sampling frequency and poor accuracy, on the other hand, another navigation system GPS has high accuracy compared to ADS but lower sampling frequency.Kalman Filter is used to integrate and minimize the errors of the two navigation systems. By this integration a navigation system with high sampling frequency and high accuracy is aimed. Another object is to calculate the wind speed with high accuracy.

Indoor monocular mobile robot navigation based on color landmarks

A robot landmark navigation system based on monocular camera was researched theoretically and experimentally.First the landmark setting and its data structure in programming was given;then the coordinates of them getting by robot and global localization of the robot was described;finally experiments based on Pioneer III mobile robot show that this system can work well at different topographic situation without lose of signposts.

Global Mapper软件在第28次南极考察中的应用

Global Mapper是一个地理信息管理与应用软件,结合其在第28次南极考察中的应用,介绍了软件的基本功能。软件提供的链接可以让用户方便地下载诸如全球地貌网格数据之类的科学数据。软件支持数据格式繁多,并可以对这些文件进行大地坐标投影转换并输出,可以进行点、线、面和等值线图的绘制并兼有简单的空间分析功能。此外,软件还可以连接GPS用以辅助导航定位,具有广阔的应用前景。

中国区域电离层实时建模与分析

电离层延迟是全球卫星导航系统(GNSS)中的一个主要误差来源。为了改正电离层误差,一些GNSS应用如单频精密单点定位(PPP)和非差非组合PPP依赖于全球电离层模型(GIM)产品。然而,目前可用GIM产品的发布时间存在延迟,不适用于实时GNSS应用。为了解决这个问题,文中提出一种基于卡尔曼滤波(KF)的实时电离层建模方法,并基于中国区域116个连续运行参考站(CORS)的观测数据,生成中国区域的实时区域电离层模型(RT-RIM)。此外,由于伪距差分码偏差(DCB)与电离层延迟存在强耦合关系,还对BDS-2/3、GPS和Galileo系统的DCB进行估计。结果统计分析表明,模型输出的垂直总电子含量(VTEC)与中国科学院(CAS)的最终GIM产品一致性较好,二者差异的RMS小于2 TECU;将VTEC投影为斜向总电子含量(STEC)后,与PPP估计结果偏差的RMS在0.2~0.8 m;模型输出的卫星DCB与CAS快速产品的偏差RMS小于0.8 ns,以上结果表明本文模型具有较好的精度,能够精细描述中国区域电离层VTEC的时空变化。

GPS/Galieo/BDS多频多模PPP定位性能评估

全球导航卫星系统(GNSS)的快速发展提供了多样化的数据,多频多模精密单点定位(PPP)是今后定位的重要趋势。现对4种不同组合(GPS+BDS/GPS+Galieo/BDS+Galieo/GPS+Galieo+BDS)多频多模PPP定位性能进行评估,借助MGEX跟踪站中12个观测站60d观测数据进行静态、动态实验。结果表明,4种不同组合多频多模PPP结果均为厘米级,GPS+BDS、GPS+Galieo和BDS+Galieo双系统组合定位在N、E、U方向定位精度基本相当,且在U方向定位精度最差,三系统(GPS+Galieo+BDS)PPP结果可提高静态、动态定位精度,其中静态定位在N、E、U方向上的平均定位精度分别提升10.98%、11.82%、9.18%,动态定位在N、E、U方向上平均定位精度分别提升10.96%、7.52%、8.23%,多频多模PPP对城市复杂环境定位精度有提升效果。