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GPS/INS

About: GPS/INS is a research topic. Over the lifetime, 3554 publications have been published within this topic receiving 62784 citations.


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Journal ArticleDOI
TL;DR: This paper proposes a novel technique for estimating the missing GPS route by integrating data from the sensors available in modern smartphones, and shows that GPS/IMU integration can be accomplished with off-the-shelf navigational components.
Abstract: Commonly, navigation uses global positioning system/network (GPS) signals to determine location. In addition, GPS data can be collected over time to determine the path taken. In spite of the ubiquity of GPS signals on the earth’s surface, there are certain locations where GPS signals are not available, such as inside buildings or tunnels. Therefore, to determine accurate positioning in areas where the GPS signals are unavailable, an inertial measurement unit (IMU) can be used in conjunction with the GPS data. Modern IMUs are small enough to be contained in Microelectromechanical systems (MEMS) chips, including smartphone devices, such as iPhones. This paper studies the integration between the GPS signal and the collected data from smartphones’ MEMS sensors. It also investigates the possibility of using the integrated GPS/MEMS information to estimate route when the GPS signal is missing. We propose estimating the missing GPS signal by sensor integration of smartphone data. This paper would enhance the GPS navigation to determine exact positions even in the case of signal failures. Modern IMUs are expensive, and this paper shows that GPS/IMU integration can be accomplished with off-the-shelf navigational components. This paper proposes a novel technique for estimating the missing GPS route by integrating data from the sensors available in modern smartphones.

19 citations

Book
09 Oct 2012
TL;DR: This thesis seeks to determine it, via simulation, it is viable to aid an INS with visual measurements, and if so, how to deal with the denial of the GPS signal.
Abstract: : Inertial navigation systems and GPS system's have revolutionized the world of navigation. Inertial system's are incapable of being jammed and are the backbone of most navigation system's. GPS is highly accurate over long periods of time, and it is an excellent aid to inertial navigation system's. However, as a military force we must be prepared to deal with the denial of the GPS signal. This thesis seeks to determine it, via simulation, it is viable to aid an INS with visual measurements.

19 citations

Proceedings ArticleDOI
25 Jun 2012
TL;DR: An analysis and modelling of the inertial sensors which combines Autoregressive Filters and Wavelet De-noising is implemented and the results show a comparison between these sensor error models with real data under GPS outage conditions.
Abstract: Thanks to advances in the development of Micro-Electromechanical Systems (MEMS), it has been possible to fabricate small dimension and cheap accelerometers and gyros, which are being used in many applications where the GPS/INS integration is carried out, as for example to identify track defects, navigation, geo-referencing, agriculture, etc. Although these MEMS devices have a low-cost, they present different errors which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modelling of these errors is necessary in order to improve the system performance. In this work, Allan Variance and Power Spectral Density techniques are used to identify the random processes that affect the inertial sensor data. Once the random components are identified, they are modelled using first-order Gauss-Markov and random walk processes. Two models are assessed augmenting the states of the Extended Kalman Filter (EKF) to 6 and 9. Subsequently, another analysis and modelling of the inertial sensors which combines Autoregressive Filters and Wavelet De-noising is implemented and in this case the EKF of the loosely coupled GPS/INS integration strategy is augmented with 6, 12 and 18 states. Finally, the results show a comparison between these sensor error models with real data under GPS outage conditions.

19 citations

20 Sep 2013
TL;DR: This paper proposes a search algorithm for cycle slip detection and correction that reliably corrects all cycle sli ps in environments with both high multipath and high receiver dynamics, and enables a heading determination with an accuracy of 0.5/ baseline length.
Abstract: Low-cost GNSS receivers with patch antennas track the carrier phases of the GNSS signals with millimeterto centimeter-level accuracy. However, code multipath of several tens of metres, frequent half cycle slips, and receive r clock offsets in the order of milliseconds make reliable kinematic integer ambiguity resolution still challenging. Low-cost inertial sensors are robust against GNSS signal shadowing and benefit from a higher measurement rate but show large integration drifts due to biases in the gyroscope and acceleration measurements and, require an initializat ion with another sensor. In this paper, we couple the information of both sensors for attitude determination and propose a search algorithm for cycle slip detection and correction. The search algorithm uses double difference carrier phase, acceleration a nd gyroscope measurements, and also considers a priori information on the baseline length. The cycle slip corrections are determined such that the optimum trade-off between minimizing the squared measurement residuals and minimizing the squared baseline length residuals is found. We tested the method during various car drives. Measurement results show that the method reliably corrects all cycle sli ps in environments with both high multipath and high receiver dynamics, and enables a heading determination with an accuracy of0.5/ baseline length [m]. INTRODUCTION Attitude determination is widely performed with inertial sensors and geodetic GNSS receivers in maritime and aerospace applications. The carrier phase can be tracked with millimeter-level accuracy and, therefore, is very attract ive for precise attitude determination. Double differences ar e formed to eliminate receiver and satellite clock offsets an d biases as well as atmospheric errors. This leaves the double difference integer ambiguities and baseline coordinat es as unknowns. Teunissen developed the Least Squares Ambiguity Decorrelation Adjustment (LAMBDA) method in [1] to solve the integer least-squares problem. For attitud e determination, the success rate of ambiguity resolution ca n be further increased if the baseline length a priori informa tion is included in the search process. In [2] and [3], Teunissen developed a constrained LAMBDA method to solve the constrained integer least-squares problem. Low-cost GNSS receivers can also track the carrier phase with millimeterto centimeter-level accuracy. Consequently, they are very attractive for automotive applicati ons (e.g. heading determination of cars, Fig. 1).

19 citations

Proceedings ArticleDOI
20 Apr 1998
TL;DR: IMU alignment is addressed by examining results from two different INS error modeling approaches using actual flight test data recorded from captive pod mounted IMU and reference INU and suggesting that alignment and aided navigation can be accomplished and sustained with a navigation filter algorithm which implements the perturbation error model without an alignment manoeuvre.
Abstract: IMU alignment is addressed by examining results from two different INS error modeling approaches using actual flight test data recorded from captive pod mounted IMU and reference INU. The emphasis of this paper is alignment during the aircraft's low dynamics ground operations before takeoff. The two MS error models used to produce the alignment results are based on computer frame and perturbation error models, and are formulated to use position observations in a transfer alignment Kalman filter algorithm. The use of position observations is consistent with other navigation aides such as GPS. Performance measures used to evaluate the two INS error models' results include: filter state convergence rates, IMU navigation solution heading compared to the reference MU heading, and post-alignment unaided navigation position error growth during manoeuvres after aircraft takeoff. For all three, the perturbation error model shows better results. The results suggest that alignment and aided navigation can be accomplished and sustained with a navigation filter algorithm which implements the perturbation error model without an alignment manoeuvre.

19 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202317
202247
20219
202013
201925
201840