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Sameh Nassar - One of the best experts on this subject based on the ideXlab platform.
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A combined algorithm of improving INS error modeling and sensor measurements for accurate INS/GPS navigation
GPS Solutions, 2006Co-Authors: Sameh Nassar, Naser El-sheimyAbstract:Although the integrated system of a differential global positioning system (DGPS) and an inertial navigation system (INS) had been widely used in many geodetic navigation applications, it has sometimes a major limitation. This limitation is associated with the frequent occurrence of DGPS outages caused by GPS signal blockages in certain situations (urban areas, high trees, tunnels, etc.). In the standard mechanization of INS/DGPS navigation, the DGPS is used for positioning while the INS is used for attitude determination. In case of GPS signal blockages, positioning is provided using the INS instead of the GPS until satellite signals are obtained again with sufficient accuracy. Since the INS has a very short-time accuracy, the accuracy of the provided INS navigation parameters during these periods decreases with time. However, the obtained accuracy in these cases is totally dependent on the INS error model and on the quality of the INS sensor data. Therefore, enhanced navigation parameters could be obtained during DGPS outages if better inertial error models are implemented and better quality inertial measurements are used. In this paper, it will be shown that better INS error models are obtained using autoregressive processes for modeling inertial sensor errors instead of Gauss–Markov processes that are implemented in most of the current inertial systems and, on the other hand, that the quality of inertial data is improved using wavelet multi-resolution techniques. The above two methods are discussed and then a combined algorithm of both techniques is applied. The performance of each method as well as of the combined algorithm is analyzed using land-vehicle INS/DGPS data with induced DGPS outage periods. In addition to the considerable navigation accuracy improvement obtained from each single method, the results showed that the combined algorithm is better than both methods by more than 30%.
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wavelet analysis for improving ins and ins DGPS navigation accuracy
Journal of Navigation, 2005Co-Authors: Sameh Nassar, Naser ElsheimyAbstract:The integration of the Global Positioning System (DGPS) with an Inertial Navigation System (INS) has been implemented for several years. In an integrated INS/DGPS system, the DGPS provides positions while the INS provides attitudes. In case of DGPS outages (signal blockages), the INS is used for positioning until the DGPS signals are available again. One of the major issues that limit the INS accuracy, as a stand-alone navigation system, is the level of sensor noise. The problem with inertial data is that the required signal is buried into a large window of high frequency noise. If such noise component could be removed, the overall inertial navigation accuracy is expected to improve considerably. The INS sensor outputs contain actual vehicle motion and sensor noise. Therefore, the resulting position errors are proportional to the existing sensor noise and vehicle vibrations. In this paper, wavelet techniques are applied for de-noising the inertial measurements to minimize the undesirable effects of sensor noise and other disturbances. To test the efficiency of inertial data de-noising, two road vehicle INS/DGPS data sets are utilized. Compared to the obtained position errors using the original inertial measurements, the results showed that the positioning performance using de-noised data improves by 34%-63%.
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improving positioning accuracy during kinematic DGPS outage periods using sins DGPS integration and sins data de noising
Survey Review, 2004Co-Authors: Sameh Nassar, Aboelmagd Noureldin, Naser ElsheimyAbstract:Abstract In the standard integration of a Differential Global Positioning System (DGPS) and a Strapdown Inertial Navigation System (SINS), the DGPS provides position information while the SINS provides attitude information. In addition, the DGPS measurements are used to estimate the inertial sensors systematic errors and the SINS is used to detect and correct GPS cycle slips. In case of GPS signal blockages, the SINS is used instead for positioning as a stand-alone system until the GPS signals are available again. To obtain accurate positions during DGPS outages, near real-time (or post-mission) techniques should be applied, where these techniques are known as bridging algorithms. In such algorithms, new and improved positions of the outage periods are estimated. In this paper, two different bridging methods are used namely: backward smoothing and parametric modeling. An SINS/DGPS data collected with a van has been used in the analysis. The results show that both bridging algorithms reduce the SINS positi...
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IMPROVING POSITIONING ACCURACY DURING KINEMATIC DGPS OUTAGE PERIODS USING SINS/DGPS INTEGRATION AND SINS DATA DE-NOISING
Survey Review, 2004Co-Authors: Sameh Nassar, Aboelmagd Noureldin, Naser El-sheimyAbstract:Abstract In the standard integration of a Differential Global Positioning System (DGPS) and a Strapdown Inertial Navigation System (SINS), the DGPS provides position information while the SINS provides attitude information. In addition, the DGPS measurements are used to estimate the inertial sensors systematic errors and the SINS is used to detect and correct GPS cycle slips. In case of GPS signal blockages, the SINS is used instead for positioning as a stand-alone system until the GPS signals are available again. To obtain accurate positions during DGPS outages, near real-time (or post-mission) techniques should be applied, where these techniques are known as bridging algorithms. In such algorithms, new and improved positions of the outage periods are estimated. In this paper, two different bridging methods are used namely: backward smoothing and parametric modeling. An SINS/DGPS data collected with a van has been used in the analysis. The results show that both bridging algorithms reduce the SINS positi...
Naser El-sheimy - One of the best experts on this subject based on the ideXlab platform.
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A combined algorithm of improving INS error modeling and sensor measurements for accurate INS/GPS navigation
GPS Solutions, 2006Co-Authors: Sameh Nassar, Naser El-sheimyAbstract:Although the integrated system of a differential global positioning system (DGPS) and an inertial navigation system (INS) had been widely used in many geodetic navigation applications, it has sometimes a major limitation. This limitation is associated with the frequent occurrence of DGPS outages caused by GPS signal blockages in certain situations (urban areas, high trees, tunnels, etc.). In the standard mechanization of INS/DGPS navigation, the DGPS is used for positioning while the INS is used for attitude determination. In case of GPS signal blockages, positioning is provided using the INS instead of the GPS until satellite signals are obtained again with sufficient accuracy. Since the INS has a very short-time accuracy, the accuracy of the provided INS navigation parameters during these periods decreases with time. However, the obtained accuracy in these cases is totally dependent on the INS error model and on the quality of the INS sensor data. Therefore, enhanced navigation parameters could be obtained during DGPS outages if better inertial error models are implemented and better quality inertial measurements are used. In this paper, it will be shown that better INS error models are obtained using autoregressive processes for modeling inertial sensor errors instead of Gauss–Markov processes that are implemented in most of the current inertial systems and, on the other hand, that the quality of inertial data is improved using wavelet multi-resolution techniques. The above two methods are discussed and then a combined algorithm of both techniques is applied. The performance of each method as well as of the combined algorithm is analyzed using land-vehicle INS/DGPS data with induced DGPS outage periods. In addition to the considerable navigation accuracy improvement obtained from each single method, the results showed that the combined algorithm is better than both methods by more than 30%.
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IMPROVING POSITIONING ACCURACY DURING KINEMATIC DGPS OUTAGE PERIODS USING SINS/DGPS INTEGRATION AND SINS DATA DE-NOISING
Survey Review, 2004Co-Authors: Sameh Nassar, Aboelmagd Noureldin, Naser El-sheimyAbstract:Abstract In the standard integration of a Differential Global Positioning System (DGPS) and a Strapdown Inertial Navigation System (SINS), the DGPS provides position information while the SINS provides attitude information. In addition, the DGPS measurements are used to estimate the inertial sensors systematic errors and the SINS is used to detect and correct GPS cycle slips. In case of GPS signal blockages, the SINS is used instead for positioning as a stand-alone system until the GPS signals are available again. To obtain accurate positions during DGPS outages, near real-time (or post-mission) techniques should be applied, where these techniques are known as bridging algorithms. In such algorithms, new and improved positions of the outage periods are estimated. In this paper, two different bridging methods are used namely: backward smoothing and parametric modeling. An SINS/DGPS data collected with a van has been used in the analysis. The results show that both bridging algorithms reduce the SINS positi...
Naser Elsheimy - One of the best experts on this subject based on the ideXlab platform.
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heading accuracy improvement of mems imu DGPS integrated navigation system for land vehicle
IEEE ION Position Location and Navigation Symposium, 2008Co-Authors: Naser ElsheimyAbstract:Many researches indicated that in land vehicle-based MEMS IMU/DGPS integrated navigation system, the vehicle heading is unobservable and its error can grow significantly fast with time, if the vehicle moves with only slow changes in attitude and acceleration, e.g. the vehicle moving along a straight road at almost constant velocity. In this paper, a new heading measurement is derived from the DGPS positions and this new measurement can improve the heading accuracy of MEMS IMU/DGPS integrated navigation system for land vehicle. However, the DGPS-derived heading will have a significant deviation from the true heading value while the vehicle makes a turn. Thus a sequential Kalman filter is proposed to process the DGPS position and heading measurements in a sequential order with MEM IMU measurements. This ensures the DGPS position measurements still can be used in the KF even if the DGPS heading measurements are unusable due to large deviation to the truth. To ensure the quality of the DGPS heading measurements, an innovation detection method is used to detect and reject the singular DGPS heading measurement from the sequential Kalman filter. A field test was conducted to test the effect of this new heading measurement on improving land vehicle heading accuracy. The test results showed that this new type of measurement can significantly reduce the heading error of MEMS IMU/DGPS integrated navigation solution from about 5 deg to less than 1 deg. Test results also showed that the innovation detection method can effectively control the quality of DGPS heading measurement. Without this control, the singular heading measurement would lead to a heading error as large as 100 deg. In summary, the introduction of DGPS-derived new heading measurement and the innovation detection method investigated in this paper can significantly improve the accuracy and reliability of the heading parameter in land vehicle MEMS IMU/DGPS integrated navigation system.
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wavelet analysis for improving ins and ins DGPS navigation accuracy
Journal of Navigation, 2005Co-Authors: Sameh Nassar, Naser ElsheimyAbstract:The integration of the Global Positioning System (DGPS) with an Inertial Navigation System (INS) has been implemented for several years. In an integrated INS/DGPS system, the DGPS provides positions while the INS provides attitudes. In case of DGPS outages (signal blockages), the INS is used for positioning until the DGPS signals are available again. One of the major issues that limit the INS accuracy, as a stand-alone navigation system, is the level of sensor noise. The problem with inertial data is that the required signal is buried into a large window of high frequency noise. If such noise component could be removed, the overall inertial navigation accuracy is expected to improve considerably. The INS sensor outputs contain actual vehicle motion and sensor noise. Therefore, the resulting position errors are proportional to the existing sensor noise and vehicle vibrations. In this paper, wavelet techniques are applied for de-noising the inertial measurements to minimize the undesirable effects of sensor noise and other disturbances. To test the efficiency of inertial data de-noising, two road vehicle INS/DGPS data sets are utilized. Compared to the obtained position errors using the original inertial measurements, the results showed that the positioning performance using de-noised data improves by 34%-63%.
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improving positioning accuracy during kinematic DGPS outage periods using sins DGPS integration and sins data de noising
Survey Review, 2004Co-Authors: Sameh Nassar, Aboelmagd Noureldin, Naser ElsheimyAbstract:Abstract In the standard integration of a Differential Global Positioning System (DGPS) and a Strapdown Inertial Navigation System (SINS), the DGPS provides position information while the SINS provides attitude information. In addition, the DGPS measurements are used to estimate the inertial sensors systematic errors and the SINS is used to detect and correct GPS cycle slips. In case of GPS signal blockages, the SINS is used instead for positioning as a stand-alone system until the GPS signals are available again. To obtain accurate positions during DGPS outages, near real-time (or post-mission) techniques should be applied, where these techniques are known as bridging algorithms. In such algorithms, new and improved positions of the outage periods are estimated. In this paper, two different bridging methods are used namely: backward smoothing and parametric modeling. An SINS/DGPS data collected with a van has been used in the analysis. The results show that both bridging algorithms reduce the SINS positi...
Francisco J. Restivo - One of the best experts on this subject based on the ideXlab platform.
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Evaluation of a real time DGPS data server
European Conference on the Use of, 2004Co-Authors: Manuel G Soares, Benedita Malheiro, Francisco J. RestivoAbstract:The goal of the this paper is to show that the DGPS data Internet service we designed and developed provides campus-wide real time access to Differential GPS (DGPS) data and, thus, supports precise outdoor navigation. First we describe the developed distributed system in terms of architecture (a three tier client/server application), services provided (real time DGPS data transportation from remote DGPS sources and campus-wide data dissemination) and transmission modes implemented (raw and frame mode over TCP and UDP). Then we present and discuss the results obtained and, finally, we draw some conclusions.
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an internet DGPS service for precise outdoor navigation
Emerging Technologies and Factory Automation, 2003Co-Authors: Manuel G Soares, Benedita Malheiro, Francisco J. RestivoAbstract:The goal of the work presented in this paper is to provide mobile platforms within our campus with a GPS based data service capable of supporting precise outdoor navigation. This can be achieved by providing campus-wide access to real time Differential GPS (DGPS) data. As a result, we designed and implemented a three-tier distributed system that provides Internet data links between remote DGPS sources and the campus and a campus-wide DGPS data dissemination service. The Internet data link service is a two-tier client/server where the server-side is connected to the DGPS station and the client-side is located at the campus. The campus-wide DGPS data provider disseminates the DGPS data received at the campus via the campus Intranet and via a wireless data link. The wireless broadcast is intended for portable receivers equipped with a DGPS wireless interface and the Intranet link is provided for receivers with a DGPS serial interface. The application is expected to provide adequate support for accurate outdoor campus navigation tasks.
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Real Time Internet DGPS Service
2003Co-Authors: Manuel G Soares, Benedita Malheiro, Francisco J. RestivoAbstract:The accuracy of the Navigation Satellite Timing and Ranging (NAVSTAR) Global Positioning System (GPS) measurements is insufficient for many outdoor navigation tasks. As a result, in the late nineties, a new methodology – the Differential GPS (DGPS) – was developed. The differential approach is based on the calculation and dissemination of the range errors of the GPS satellites received. GPS/DGPS receivers correlate the broadcasted GPS data with the DGPS corrections, granting users increased accuracy. DGPS data can be disseminated using terrestrial radio beacons, satellites and, more recently, the Internet. Our goal is to provide mobile platforms within our campus with DGPS data for precise outdoor navigation. To achieve this objective, we designed and implemented a three-tier client/server distributed system that establishes Internet links with remote DGPS sources and performs campus-wide dissemination of the obtained data. The Internet links are established between data servers connected to remote DGPS sources and the client, which is the data input module of the campus-wide DGPS data provider. The campus DGPS data provider allows the establishment of both Intranet and wireless links within the campus. This distributed system is expected to provide adequate support for accurate (submetric) outdoor navigation tasks.
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ETFA (1) - An internet DGPS service for precise outdoor navigation
EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696), 1Co-Authors: Manuel G Soares, Benedita Malheiro, Francisco J. RestivoAbstract:The goal of the work presented in this paper is to provide mobile platforms within our campus with a GPS based data service capable of supporting precise outdoor navigation. This can be achieved by providing campus-wide access to real time Differential GPS (DGPS) data. As a result, we designed and implemented a three-tier distributed system that provides Internet data links between remote DGPS sources and the campus and a campus-wide DGPS data dissemination service. The Internet data link service is a two-tier client/server where the server-side is connected to the DGPS station and the client-side is located at the campus. The campus-wide DGPS data provider disseminates the DGPS data received at the campus via the campus Intranet and via a wireless data link. The wireless broadcast is intended for portable receivers equipped with a DGPS wireless interface and the Intranet link is provided for receivers with a DGPS serial interface. The application is expected to provide adequate support for accurate outdoor campus navigation tasks.
Han-shue Tan - One of the best experts on this subject based on the ideXlab platform.
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a low order DGPS based vehicle positioning system under urban environment
IEEE-ASME Transactions on Mechatronics, 2006Co-Authors: Jihua Huang, Han-shue TanAbstract:The vehicle positioning system is a key component in functions such as vehicle guidance, driver alert and assistance, and vehicle automation. Since installing a low-cost global positioning system (GPS) or inertial navigation system (INS) unit is becoming a common practice in vehicle applications, its involvement in vehicle guidance and vehicle safety deserves a closer investigation. Typical vehicle applications require high reliability, low cost, and sufficient accuracy under all operational conditions. For GPS-based positioning, urban driving with its complicated maneuvers, frequent GPS blockage, and multipath, are some of the most difficult driving environments. This paper explores the feasibility of a low-order vehicle positioning system functioning under an urban environment. The equipped vehicle has a midrange differential GPS (DGPS) unit and few relatively simple in-vehicle sensors. A low-order integration is explored by utilizing a vehicle model-based extended Kalman filter (EKF) to incorporate in-vehicle motion sensors and to largely avoid direct integration of INS signals. Further, the characteristics of DGPS measurements under urban environments are investigated, and novel DGPS noise processing techniques are proposed to reduce the chances of exposing the EKF to undesirable DGPS measurements due to common DGPS problems such as blockage and multipath. A resulting fourth order EKF based positioning system is successfully implemented in the test vehicle to demonstrate the feasibility of the proposed design. Experimental results illustrate the ability of the system to meet the accuracy and robustness requirements in the presence of blockage and multipath under a typical urban driving environment
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DGPS/INS-based Vehicle Positioning with Novel DGPS Noise Processing
2006 American Control Conference, 2006Co-Authors: Han-shue Tan, Jihua HuangAbstract:The vehicle positioning system is a key component in such functions as vehicle guidance, driver alert and assistance, as well as vehicle automation. Typical vehicle applications require high reliability, low cost and sufficient accuracy under all operation conditions. This paper explores the feasibility of a low-order vehicle positioning system functioning under urban driving environments. The equipped vehicle will have a mid-range differential GPS (DGPS) unit and a few relatively simple in-vehicle sensors. A low-order DGPS/INS integration is explored by considering only vehicle longitudinal, lateral and yaw motions. The characteristics of DGPS measurements under urban environment are investigated and novel DGPS noise processing techniques are proposed to address common DGPS problems such as blockage and multipath. A resulting 4th-order Kalman filter-based DGPS/INS integration is successfully implemented in the test vehicle to demonstrate the feasibility of the proposed design. Experimental results illustrate the ability of the system to meet the accuracy and robustness requirements under a typical urban driving environment.