Magnetic compass fault detection method for GPS/INS/magnetic compass integrated navigation systems

For the integrated navigation system, the correctness and the rapidity of fault detection for each sensor subsystem affects the accuracy of navigation. In this paper, a novel fault detection method for navigation systems is proposed based on Gaussian Process Regression (GPR). A GPR model is first used to predict the innovation of a Kalman filter. To avoid local optimisation, particle swarm optimisation is adopted to find the optimal hyper-parameters for the GPR model. The Fault Detection Function (FDF), which has an obvious jump in value when a fault occurs, is composed of the predicted innovation, the actual innovation of the Kalman filter and their variance. The fault can be detected by comparing the FDF value with a predefined threshold. In order to verify its validity, the proposed method is used in a SINS/GPS/Odometer integrated navigation system. The comparison experiments confirm that the proposed method can detect a gradual fault more quickly compared with the residual chi-squared test. Thus the navigation system with the proposed method gives more accurate outputs and its reliability is greatly improved.

Many researches on use of local ground navigation systems can be found to overcome vulnerability of GNSS. Effective use of an altimeter is proposed in GNSS/DME integrated navigation systems. A weighted DOP based on statistics of measurement error is derived for a given vehicle motion trajectory. From the derived DOP, the vertical error is estimated. By comparing the estimated vertical error with error specification of the altimeter, use of the altimeter is determined in the GPS/DME integrated navigation systems. In order to show effectiveness of the proposed method, 50 times Monte-Carlo simulations were performed for a GPS/DME integrated navigation system. The results show that the proposed method gives more accurate navigation outputs when the number of GPS satellites in view varies.

In the integrated inertial navigation system (INS) and celestial navigation system (CNS), the attitudes and positions of probes are estimated based on the auxiliary measurement of an infrared Earth sensor. The poor accuracy of the infrared Earth sensor compared to that of the star sensor significantly limits the navigation accuracy of the integrated navigation system. This paper proposes a novel INS/CNS integrated navigation system that uses the specific force with noncumulative error to correct infrared Earth measurements. The probe azimuth angle and elevation angle relative to the Earth's inertial frame are first estimated according to the specific force provided by the INS to filter the infrared Earth sensor's measurement error. Then, the corrected infrared Earth measurement assists the CNS to obtain accurate celestial measurements. The integrated INS/CNS navigation system in the tightly coupled mode finally estimates the accurate probe attitude and position. Compared to the integrated navigation system, which directly uses the uncorrected infrared Earth measurement, the yaw, pitch, and roll angle are improved under the proposed method by 76.73%, 77.64%, and 75.39% on average, respectively; the latitude and longitude estimation errors improve under the proposed method by 70.44% and 61.92% on average, respectively. In short, the proposed method is a feasible and highly accurate approach to the INS/CNS integrated navigation system.

In this article, a prediction method based on a radial basis function neural network and an improved unscented Kalman filter, is proposed to improve the accuracy of position and velocity of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system, especially in the presence of GPS signal outages. The improved unscented Kalman filter based on the adaptive theory is adopted to enhance the positioning accuracy of the GPS/SINS integrated navigation system when a GPS signal is available. A radial basis function neural network and a non-stationary time series analysis are used to predict and compensate for the positioning error of the GPS/SINS integration in the presence of GPS signal outages to improve the reliability of the navigation system. The effectiveness of the proposed method is verified by the simulation experiment and vehicle test. The simulation and test results show that the proposed method can improve the position accuracy and velocity accuracy in different GPS outage time periods.

The objective of this work is to introduce an autonomous Hovercraft with minimum Energy consumption. To achieve this goal, a computer simulation in addition to practical testing of a simple hovercraft model have been carried out. A mathematical model for the hovercraft is considered and simulated in the MATLAB/SIMULINK environment. A navigation system with Global Positioning System (GPS) integrated with an Inertial Measurement Unit (IMU) sensors are used to monitor the speed, position, and the direction of the hovercraft for the autonomous operation. Two motors with propellers are used for the lifting and thrust systems, while a third one is used for the rudder movement that controls the direction. Specific resistance (Ɛ) index is used to test the hovercraft performance. The results of the practical experiments of moving the hovercraft between two and three points are compared with that of the computer simulation. The distance error from the actual target has been found to be in the range of about 18%, which proves the idea. It should be noted that this significant error is due to the fact that the GPS considered is a low price commercial one and using more accurate one will result in more satisfactory results. Based on the computer simulation and practical testing results, a look up table has been prepared to help in deriving an algorithm for controlling the RPM of lifting and thrust Fans based on the minimum optimum specific resistance.

Celestial navigation system (CNS) is a completely autonomous navigation technology with strong anti-interference ability and high navigation accuracy, which has a great application prospect. Aim at defect of traditional integrated navigation system using attitude angle measurement celestial navigation system and strapdown inertial navigation system (SINS), which can only correct of strapdown inertial navigation system’s gyro drift. This paper proposes an improved integrated navigation system that add double-star positioning celestial navigation to traditional SINS/CNS integrated navigation system, meanwhile, introduces the fault detection technology based on statistical distance to solve the problem that inaccuracy of measurement information leads to the integrated navigation system’s performance degradation. By analyzing the simulation results, the improved navigation system can inhibit divergence of system and obtain high accurate and stable navigation information.

Global Navigation Satellite Systems (GNSS) has been the primary positioning solution for Unmanned Aerial Vehicles (UAVs) due to their worldwide coverage, high precision and lightweight receivers. However, GNSS is prone to electromagnetic interference and malicious assaults, including jamming or spoofing because of its low signal-to-noise ratio (SNR). To ensure the continuity and protection of UAV operations, using redundant navigation systems is essential. In recent years, the phased array radio system (PARS) has established itself as a local navigation solution. PARS is robust towards malicious assaults because of an much higher SNR than GNSS regarding directed and encrypted transmission. An essential factor of PARS is that the orientation of the radio antenna at a ground station needs to be precisely determined to obtain the correct positioning of UAVs. This paper presents a method for extending a previously proposed calibration algorithm to estimate the ground antenna orientation with an inertial navigation system (INS) aided by redundant positioning sensors (GNSS, PARS or barometer) using a multiplicative extended Kalman filter (MEKF) so that the calibration can be activated during flights whenever GNSS is available. In other words, the proposed navigation system is essentially an aided-INS which switches between two modes depending on the availability of GNSS: calibration and GNSS aiding mode when GNSS is available (Mode 1) and PARS and barometer aiding mode when GNSS is unavailable (Mode 2). Considering that the navigation system needs to include the effect of Earth’s curvature for a long-distance flight, PARS horizontal measurement and the barometer measurement were treated independently, and the navigation equations were propagated in Earth Centred Earth Fixed (ECEF) frame. The independent treatment of barometer measurement, and the propagation in ECEF frame were also beneficial when using multiple ground antennas to have a common reference point and reference frame. The proposed method was validated using data (Inertial Measurement Unit (IMU), GNSS, PARS, Pixhawk autopilot (including barometer) measurements) collected during a field test. In the validation, GNSS was made available at the middle of the flight and the calibration mode was activated for 200s. The proposed navigation system successfully estimated the precise orientation of multiple ground antennas and the navigation solutions were verified using GNSS and Pixhawk autopilot solutions as ground truth.

We describe an integrated navigation system based on Global Navigation Satellite Systems (GNSS), an Inertial Navigation System (INS) and terrestrial ranging technologies that can support accurate and seamless indoor-outdoor positioning. To overcome severe multipath disturbance in indoor environments, Locata technology is used in this navigation system. Such a “Locata-augmented” navigation system can operate in different positioning modes in both indoor and outdoor environments. In environments where GNSS is unavailable, e.g. indoors, the proposed system is designed to operate in the Locata/INS “loosely-integrated” mode. On the other hand, in outdoor environments, all GNSS, Locata and INS measurements are available, and all useful information can be fused via a decentralised Federated Kalman filter. To evaluate the proposed system for seamless indoor-outdoor positioning, an indoor-outdoor test was conducted at a metal-clad warehouse. The test results confirmed that the proposed navigation system can provide continuous and reliable position and attitude solutions, with the positioning accuracy being better than five centimetres.

This paper proposed an efficient quality control algorithm for the GNSS/INS integrated navigation system, the system therefore can be efficiently and reliably applied in complex urban environment with shelters, multipath, reflections and data loss. The quality control algorithm consists of GNSS and INS modules. In order to reduce the adverse influence from abnormal GNSS data, a Kalman Filter with a Fault Detection and Exclusion (FDE) procedure is proposed to enhance the system reliability and stability. The stochastic model for Kalman Filter is determined by Allan Variance analysis to reduce the time dependent ramp error of INS data. In comparison with traditional GNSS/INS integrated system, the new system can detect and repair GNSS outliers in real-time and also can alleviate the INS ramp errors when GNSS signals are interfered with. In order to evaluate the performance of the proposed navigation system, a field test has been conducted in Sydney urban area. The performance of the proposed navigation system and the effectiveness of the FDE algorithm that was applied to the GNSS data with high fault rate and slight data loss were evaluated. The results show that the proposed algorithm with the optimal quality control design can give reliable navigation solution that is better than that with the normal quality control design.KeywordsFault detection and exclusionAllan varianceAbrupt errorSlowly growing error

Magnetic nanoparticles (MNPs) are a promising candidate for use as carriers in drug delivery systems. A navigation system with real-time actuation and monitoring of MNPs is inevitably required for more precise targeting and diagnosis. In this paper, we propose a novel electromagnetic navigation system with a coil combined with a soft magnetic core. This system can be used for magnetic particle imaging (MPI) and electromagnetic actuator functions with a higher steering force and enhanced monitoring resolution. A soft magnetic core with coils can increase the magnetic gradient field. However, this also generates harmonic noise, which makes it difficult to acquire MNP monitoring signals with MPI. Therefore, the use of amplitude modulation magnetic particle imaging (AM MPI) is suggested. AM MPI uses a low-amplitude excitation field combined with a low-frequency drive field. Using this system, the measured signal becomes less sensitive to the soft magnetic core. Based on the new MPI scheme and the combination of the coil with the magnetic cores, the proposed navigation system can implement one-dimensional (1-D) MNP navigation and 2-D MPI. The proposed navigation system can shorten the 1-D guidance time by about 25% for MNPs in the size range of 45-60 nm and give an improved 2-D imaging resolution of 43%, compared with an air-coil structure.

Integrated navigation systems have evolved in response to the increasing requirements for more accurate navigation of marine survey vessels. Some systems have been better than others in terms of choice of devices for combination, or in mathematical handling of data from the respective sensors, but all have been inflexible in terms of interchange of sensor types or adaptation of new devices. This paper studies the basic philosophy of navigation system design with primary consideration given to system objectives and control structure. The result is a sensor-independent approach to integrated navigation system design. INTRODUCTION At this point in time, there is no universal aid to navigation which can provide continuous position fixes and velocities on a worldwide, 24-hour per day basis, and still deliver the accuracies required by all users. There are several systems which offer accuracy and continuity, but operate over a limited range; e.g., doppler satellites yield worldwide coverage but give only periodic fix updates; while VLF radio systems yield nearly continuous, worldwide coverage but lack the accuracy required for precision navigation. The Global Positioning System (GPS), promises to give simultaneous solutions to many of these problems, but commercial availability is not likely to be realized before the late 1980's. The approach taken to meet user requirements in precise navigation has been the "integrated navigation system" a combination of two or more different navigation subsystems. This paper deals with the philosophy of integrated system design, reviews the deficiencies in some past approaches to system integration, and describes a design structure which permits flexibility in the choice of sensor subsystems and provides for longer product lifetime. CATEGORIES OF NAVIGATION AIDS Since the earliest days of navigation, mariners have used tools to assist in determining their position (position fix) and in setting and keeping a course over a period of time to reach a desired new position (dead reckoning). Ocean voyages depended upon natural phenomena, with celestial observations for position reference and magnetic compass directions to maintain headings. Local navigation (piloting) has always used line-of-sight reference to coastline features or reference markers to maintain a desired course from successive triangulation bearings. Twentieth century techniques have considerably improved life for the navigator, extending operation on a 24-hour per day, all-weather basis while increasing the accuracy of measurement. Three techniques of measurement form the basis for most of the navigation aids currently in use: radio wave systems, which use broadcast wavelength as a "yardstick" for distance or velocity measurements between the navigator and known reference points; acoustic systems, which perform range or rangerate measurements based on propogation time of sound through water; and gyroscopic systems, which measure orientation and angular velocities within the Earth's gravitational field. The following paragraphs describe systems from all of these categories, giving some specific strengths and weaknesses of each system type.

Considering the conventional federated filtering‐based fault‐tolerant integrated navigation system is difficult to be implemented by serial data processing circuits, this paper presents navigation switching strategy‐based SINS/GPS/ADS/DVL fault‐tolerant integrated navigation system to guarantee the reliability of integrated navigation system under sensor faults. When sensor failure appears, SINS and fault‐free sensors are selected successively to form an integrated navigation system, such that reliable navigation parameters can be obtained. The simulation tests are implemented to verify that the SINS/GPS/ADS/DVL integrated navigation system can provide reliable navigation parameters when ADS and DVL are disabled.

Embedded system has outstanding characteristics in real-time, portability, application specificity and resource possession of the system. The application of embedded technology in integrated navigation system can make the system smaller and more specific, therefore, this paper designs and implements BDS /GPS/SINS integrated navigation system based on embedded system. The BDS/GPS/SINS integrated navigation system can combine the advantages of BDS, GPS and SINS with higher precision and better stability. The system design covers the hardware and software, including the overall design of the hardware, the selection of the sensor module, the algorithmic analysis of the software and the system transplant. The precision and reliability of BDS/GPS/SINS integrated navigation system were tested and verified by dynamic experiment. The results show that the error range of BDS/GPS/SINS integrated navigation system in longitude, latitude and height was better than GPS/SINS navigation system.

In connection with the increasing complexity of aircraft navigation support, with growing demands placed on them, it is increasingly necessary to develop integrated navigation data processing system by solving synthesis problems based on optimal filtering methods. One of the promising ways to improve aircraft navigation support is to create an integrated navigation system (INS). In this work the triadic structure of a promising integrated navigation system based on inertial and satellite technologies is proposed. Combining nautical meters as part of the triad concept allows the flexible use of various navigation data processing algorithms and trajectory optimization ones at different stages of flight. Based on optimal filtering theory methods the integrated navigation data processing algorithm, which is an extended Kalman filter, is synthesized. A distinctive feature of the algorithm is that the variables of the state vector which are to be measured, are the errors in the determination of appropriate navigation and timing parameters. Priori information about the dynamics of errors is more reliably known than the one about aircraft motion variables. It is shown that the use of the proposed navigation system as a navigation aid for problem solving of highly accurate aircraft position indication satisfies the requirements for navigation and timing data accuracy. The imitating statistical modeling of optimal filtering algorithm of the triad integrated system is carried out. The accuracy characteristics of subsystems for different operating configurations of the constellation are given. Analysis of the results of the accuracy characteristics study of INS in various operating conditions has showed that the positioning accuracy in the navigation computer is up to date satellite navigation receivers.

A multi-sensor integrated solution that combine complementary features of the Global Positioning System (GPS), inertial navigation system (INS), and magnetometer is presented due to GPS-aided inertial navigation system (INS) provides poor observability of heading angle. In addition, Based on the principle of federated Kalman filtering and Adaptive Extended Kalman Filter, the algorithm is presented also for accuracy of positioning and attitude, rapidity, and error tolerance of the navigation system. The algorithm is implemented in the integrated navigation system. Experimental results show that the observability issue is solved and improvement in accuracy.