Figure 3 - uploaded by Duc-Tan Tran
Content may be subject to copyright.
Source publication
Due to the strong growth of MEMS technology, the Inertial Navigation System (INS) is widely applied to navigation and guidance of aircraft movements. However, there are existing errors in the accelerometer and gyroscope signals that cause unacceptable drifts. To minimize these effects on the INS system, a GPS is usually employed simultaneously with...
Context in source publication
Context 1
... discrete INS algorithm was developed in our lab in order to develop a completed Inertial Measurement Unit (IMU). The detail of this discrete algorithm will not be presented in this paper. B. Global Positioning System (GPS) The GPS consists of 24 satellites which fly above the surface of the Earth at the height 19.200 km in order to acquire the position of the aircraft (latitude, longitude and height) [2]. Radio signals often hardly transmit over solid buildings, tunnels...To get the correct position of the aircraft; it requires at least four satellites. They can separate the GPS into three segments (see Fig. 3): - Space segment: consists of 24 satellites. - Control segment: ground control - User segment: receiver (civil and military purposes) accelerometer errors. Therefore, in long-term navigation applications, the INS works with the aid of other systems such as radio navigation systems (Loran, Tacan), satellite navigation systems (GPS, GLONASS). The important advantage of these systems is stable performance. Consequently, there is a great need for integration of INS and one of these systems. The integration of INS and GPS is considered an optimal combination. The heart of integrated system is Kalman algorithm [4]. The Kalman filter is a multiple input, multiple output digital filter that can optimally estimate in real time the states of the system based on its noisy outputs. These states are position errors (latitude, longitude, height) and velocity errors (V N , V E , V D ) of the INS. The GPS output is used as a tool to estimate the error in the INS and to correct the error as much as possible. We call this is the GPS-aided INS system configuration [8], 9]. Looking at the state space ...
Similar publications
Global Navigation Satellite System (GNSS) receivers are now widely used for navigation and speed measurements. General public and companies which use GNSS rely not only on positional accuracy but also on speed accuracy. Manufacturers of GNSS receivers supply speed accuracy parameters in the relevant data sheets. However, little information is provi...
Although experimental results have demonstrated that redundant MEMS-IMUs integrated with GPS are an efficient way to improve navigation performances, the precise relationship between the number of sensors employed and the accuracy enhancement remains unclear. This article aims at demonstrating, with the help of simulations, that multiple MEMS-IMU s...
Recently, many low-cost micro electro mechanical systems (MEMS) IMUs have emerged for only several hundred US dollars. In comparison to high-end IMUs, an entire Inertial Navigation System (INS) can be implemented with smaller size/volume, lower weight and costs. On the other hand, they have a relatively lower accuracy due to their larger systematic...
The impact of natural disasters and other adverse events on road infrastructure leads to a partial reduction or complete renunciation of its working capacity. Currently, there is no online-based information system to disclose and manage traffic in the event of a problem or disruption of a transport segment from the road infrastructure. The main pur...
Launched in December 2014 atop a Delta IV Heavy from the Kennedy Space Center, the Orion vehicle’s Exploration Flight Test 1 successfully completed the objective to stress the system by placing the uncrewed vehicle on a high-energy parabolic trajectory, replicating conditions similar to those that would be experienced when returning from an asteroi...
Citations
... Bộ lọc Kalman được sử dụng trong rất nhiều lĩnh vực và ứng dụng khác nhau [9][10][11][12][13]. Mô hình trạng thái động biểu diễn động lực học của mô hình hệ thống thời gian liên tục [8] ...
Phương pháp định vị sử dụng sóng âm hiện nay đang là một trong những phương pháp tối ưu nhất được sử dụng để xác định hình dạng và vị trí các vật thế dưới mặt nước. Nguyên tắc chung để xác định vị trí của vật thể là dựa vào thời gian từ lúc phát tín hiệu tới khi nhận được tín hiệu phản hồi từ vật thể và tốc độ truyền sóng âm trong môi trường nước, để xác định khoảng cách từ nguồn phát sóng âm chủ động tới vật thể cần khảo sát. Với mỗi ứng dụng người ta sử dụng hệ thống có chiều dài đường cơ sở khác nhau. Có rất nhiều nguyên nhân gây ra sai số thông tin định vị như sai số vận tốc âm thanh, sai số do góc thu của các cảm biến... Bài báo này đề cập tới phương pháp giảm các sai số nói trên sử dụng bộ lọc Kaman trong định vị thiết bị khảo sát với hệ thống chiều dài cơ sở cực ngắn (USBL). Phương pháp này dùng kết quả từ phương pháp định vị thủ công kết hợp các giá trị điều chỉnh từ bộ lọc để khắc phục những sai số khi hệ thống USBL bị gián đoạn. Giải pháp đã được kiểm chứng sử dụng dữ liệu thực nghiệm cho kết quả cải thiện vị trí đáng kể.
... B. Inertial Navigation System Inertial Navigation System, or INS is a dead reckoning system, which means it's able to estimate position, velocity and attitude information in the current from the previous know state. A typical INS system contains 2 parts: an Inertial Measurement Unit (IMU) and an algorithm by which the signals from IMU is processed and convert to the position and attitude information of the mounted object [4]. Cause the accelerations and angular rates increase with time ...
This paper focuses on identifying the position of moving objects (coordinates, roll, pitch,heading) based on parameters obtained from the ADIS 16 334 IMU and HI-204 GPS. Integrated navigation system GPS and INS uses extended Kalman filter algorithm to calculate the object's position more accurately. Furthermore, the algorithm is applied to an embedded system based on the Linux operating system. The system is built on the Beagle board kit in Linux operating system.
... Hardware configuration used in this study includes a computer, a GPS receiver, an IMU named MICRO-ISU BP3010 consisting of three ADXRS300 gyros and three ADXL210E accelerometers (as shown in Fig. 6). The calibration process for this IMU is presented in [12], [13]. The update rate of IMU and GPS is 64 Hz and 1 Hz, respectively. ...
Most inertial navigation system/global positioning system (INS/GPS) navigation systems for vehicles estimate position, velocity, and heading information from the GPS, and dead reckoning such as INS using a Kalman filter. However, it may suffer from INS noise, GPS noise and, especially, GPS outage. Map-matching is an additional facility to reduce errors caused by GPS outage. Usually, it has to trade-off between the performance and the complexity. In this paper, we have proposed a new map-matching algorithm called street tracking algorithm (STA) to not only correct the position error, but also estimate the velocity and the heading of the navigation system. When the GPS signal is lost, the Kalman filter is put in prediction mode and the STA is enabled. The raw acceleration of inertial measurement unit measured in body frame is also brought directly to STA as an input. The experimental result has shown that when GPS signal is lost, we can control the position error at around 2.5 m, and the velocity error at around 3.2 m/s. The proposed map-matching algorithm STA can be applied in various kinds of environment due to its simplicity and flexibility.
... Hardware configuration used in this study includes a computer, a GPS receiver, an IMU named MICRO-ISU BP3010 consisting of three ADXRS300 gyros and three ADXL210E accelerometers (as shown in Fig. 5). The calibration process for this IMU is presented in [9,10]. From the digital map, we determined 92 key points and 410 interpolated points for STA block. ...
When satellite’s signal outage occurs, a single GPS receiver will be unable to provide a reliable solution, and an INS/GPS system would continue to use the raw IMU data to compute a solution. Several complementary methods have been proposed to provide a system with highly accurate position, velocity, and attitude in challenging GPS environments. In our previous study [1], we have
proposed new algorithm called Street Tracking Algorithm (STA) to enhance the correctness of the integrated system. However, this algorithm can only improve the accuracy of the position of the vehicle due to its feed-forward configuration. This paper is an extended work of [1] when we proposed a feedback scheme that combines STA with the conventional INS/GPS system. In this novel
configuration, both velocity and position parameters are enhanced. The experimental result has showed that when GPS signal is lost, we can control the position error is around 2.5 m, and the velocity error is around 3.2 m/s.
... Figure 2(b) is zoom-in trajectories during this event. It can be seen that the traditional KF [6][7] [8] could not adapt with the changing of the measurement condition that lead to its trajectory is far from the reference one. In contrast, the trajectory obtained by AKF is very close to the reference one. ...
The GPS/INS integration is the good solution to provide a navigation system that has great performance in comparison with either an INS or a GPS stand-alone system. The GPS/INS integration
is often implemented by using Kalman Filter (KF). One of the most important tasks in integration of
GPS/INS is to choose the suitable measurement noise covariance matrix for use in the KF. However,
the environment can be change during the object is moving that lead to changing of the measurement
noise covariance matrix. There are several works concerned to use Adaptive Kalman filter (AKF) to
adopt with the environment changing. Unfortunately, most of these works are so complicated and
could not be applied to real-time applications. In this paper, we have proposed a simple method to use a look up table (LUT) for measurement noise covariance matrix. The LUT is built based on the number of satellites that the GPS receiver can see (No) and a carefully calibration process. The prime results proved that the AKF overcome KF in the case that the environment is changed.
... A rigid body is considered as a solid formed from a finite set of material points with deformable volume [18]. Generally, the rigid body attitude represents the direction of its principal axes relative to a reference coordinate system and its dynamics expresses the change of object orientation. ...
In this chapter, we'll focus on the attitude estimation problem of a body moving in 3D space. This study is devoted to the reconstruction of the posture (orientation), linear accelerations, positions and their cost in free ranging animal where the access to GPS locations is limited or impossible (application in Bio-logging). In this context, the chosen attitude representation is the quaternion, and the available data are issued from a triad of sensors including a 3-axis accelerometer, a 3-axis magnetometer and a 3-axis gyroscope (Inertial Measurement Unit). Three different approaches for the estimation of the quaternion from the data set are then proposed. The first one is based on an additive nonlinear observer design and uses the quaternion addition technique for updating attitude estimates. The second and the third approaches propose the design of a sliding mode observer and a complementary filter, respectively. In this case, the update of the estimates is based on a quaternion multiplication. This technique shows that it is a good alternative to address this problem and seems more appropriate for the quaternion algebra. The obtained results from both simulation and experimental studies show the efficiency of the proposed methodologies to reconstruct the attitude with a good accuracy for the Bio-logging application. Moreover, they allow estimating the linear acceleration and the energetic index of the animal. Finally the end of the chapter will be devoted to a dead reckoning approach to estimate the 3D position of pedestrian locomotion animal by exploiting only data from an inertial measurement unit. We'll show that obtained experimental results in the case of human locomotion, with an adjusted velocity, are satisfactory and remain promising for the application of this approach in the context of the Bio-logging.
... The combination of GPS and INS can tremendously improves accuracies compared to the GPS and INS when operating alone as individual navigation systems. The heart of integrated system is Kalman Filter (KF) [3,4]. The Kalman filter is a set of mathematical equations that provides estimations of past, present, and future states. ...
In this paper, the design of the low cost INS/GPS integration system is addressed with good accuracy. The Strapdown INS (SINS) and Cascade Kalman filter have been tested to ensure that the system can be operated flexibly between feed forward and feedback modes due to various GPS conditions. The vehicle motion constraints are also utilized to reduce the INS error degradation during the periods of GPS unavailability. The experiment results shown that the INS/GPS system can be applied to land applications in challenging GPS environments.
... In Vietnam, up to now, we are the only group focus on the integration of INS/GPS. Designing the general scheme of the INS/GPS system [4] (seeFig. 1).Figure 1. Scheme of the INS/GPS integration system in SIMULINK Determining the errors of the MEMS based sensors and constructing their noise model [3, 8]. ...
The development of positioning and navigation systems for moving object are of great interest and necessary for all countries. The INS/GPS integration system is a smart one that can tremendously improves accuracy compared to the GPS and INS when operating alone as individual navigation systems. After some successes in developing of INS/GPS system for vehicle, our research is focused on building a positioning and navigation system for ship. This paper is aimed to evaluate the problems we would have to face in ship navigation and the advantages we have had in this trend.
... The combination of GPS and INS can tremendously improves accuracies compared to the GPS and INS when operating alone as individual navigation systems. The heart of integrated system is Kalman Filter (KF) [3,4]. The Kalman filter is a set of mathematical equations that provides estimations of past, present, and future states. ...
In this paper, the design of the low cost INS/GPS integration system is addressed with good accuracy. The Strapdown INS (SINS) and Cascade Kalman filter have been tested to ensure that the system can be operated flexibly between feed forward and feedback modes due to various GPS conditions. The vehicle motion constraints are also utilized to reduce the INS error degradation during the periods of GPS unavailability. The experiment results shown that the INS/GPS system can be applied to land applications in challenging GPS environments.
... Có hai cấu trúc GPS hỗ trợ INS là xử lý theo kiểu vòng mở và vòng đóng như mô tả trong hình 3 và 4. Cấu trúc vòng mở cho phép thực thi dễ dàng hơn nhưng cấu trúc vòng kín lại cho kết quả chính xác hơn [6,7]. Bộ lọc Kalman là bộ lọc số nhiều lối vào và nhiều lối ra, cho phép ước lượng tối ưu các trạng thái của hệ thống theo thời gian thực khi các đầu vào bị nhiễu tác động. ...
Hiện nay, hệ thống định vị toàn cầu (GPS) đã được ứng dụng phổ biến trên thế giới nhưng một xu hướng mới xuất hiện đó là kết hợp GPS với hệ thống dẫn đường quán tính (INS) nhằm tận dụng triệt để ưu điểm và giảm thiểu sai lỗi của cả hai phương pháp này. Bài báo này đề cập tới việc nâng cao chất lượng của hệ thống dẫn đường tích hợp này nhờ sử dụng cấu trúc phản hồi vận tốc. Những thử nghiệm với dữ liệu trên các quỹ đạo thực tế cho thấy cấu trúc này đạt hiệu quả rất tốt.
