XXII ISPRS Congress 2012: Technical Commission VII

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Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/7, III/2, V/1, V/3, ICWG V/I: LOW-COST UAVS (UVSS) AND MOBILE MAPPING SYSTEMS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: THE PERFORMANCE ANALYSIS OF AN AKF BASED TIGHTLY-COUPLED INS/GPS INTEGRATED POSITIONING AND ORIENTATION SCHEME WITH ODOMETER AND NON-HOLONOMIC CONSTRAINTS Kun-Yao Peng, Cheng-An Lin, Kai-Wei Chiang

Document type:: Multivolume work

Structure type:: Chapter

outperforms either stand-alone system operated (Yang, 2008). There are different integrated schemes including loosely- coupled, tightly-coupled, and ultra-tightly coupled INS/GPS integrated strategies, have been researched and developed since the last decade (Petovello, 2003). The sustainability of INS/GPS integrated system using current commercially available micro-electro-mechanical systems (MEMS) inertial technology in typical GPS denied environments is fragile. However, the progress of MEMS inertial sensors is advanced rapidly thus the inclusion for general land vehicular navigation is bright in the future. In addition to waiting for the advanced development process of MEMS inertial sensor, some measures have been taken to increase the sustainability of MEMS INS/GPS integrated systems for vehicular applications during frequent signal blockages in software aspect (Chiang et al, 2003; Chiang and Huang, 2008). In other words, aiding the INS with other complementary sensors is critical to improve the accuracy of inertial based navigation systems. Choosing an appropriate estimation method is a key issue in developing an aided INS (Shin, 2005). 2. PROBLEM STATEMENTS It is common practice to use Extended Kalman Filter (EKF) to accomplish the data fusion. Several architectures for EKF implementations are known (Wendel and Trommer, 2004). The most common integration scheme used today is loosely-coupled (LC) integration scheme. It is the simplest way of integrating a GPS processing engine into an integrated navigation system. The GPS processing engine calculates position fixes and velocities in the local level frame and then send the solutions as measurement update to the main INS EKF. By comparing the navigation solutions provided by INS mechanization with those solutions provided by GPS processing engine, those navigation states can be optimally estimated, as shown in Figure 2, the primary advantage of LC architecture is the simplicity of its implementation, because no advanced knowledge of GPS processing is necessary. The disadvantage of implementation is that the measurement update of the integrated navigation system is only possible when four or more satellites are in view. g . Loosely-coupled INS/GPS integration architecture On the other hand, the tightly-coupled (TC) integration scheme uses a single KF to integrate GPS and IMU measurements. In the TC integration, the GPS pseudo-range and delta-range measurements are processed directly in the main KF, as shown in Figure 3. For some references, the aiding of the receiver tracking loops using velocity information provided by the INS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia is an essential characteristic of tightly-coupled scheme, too. The primary advantage of this integration is that raw GPS measurements can still be used to update the INS when less than four satellites are available. This is of special benefit in a hostile environment such as downtown areas where the reception of the satellite signals is difficult due to obstruction when the vehicle navigates in urban or suburban area. Figure 3. Tightly-coupled INS/GPS integration architecture However, according to Chiang and Huang (2008), the EKF implemented with a TC scheme may come with serious problems concerning the quality of GPS raw measurements. In other words, EKF based TC architecture is sensitive the quality of GPS raw measurements. This scenario usually takes place in urban and suburban areas because of the impact of reflected GPS measurements. Therefore, this study applied the Adaptive Kalman Filter (AKF) as the core estimator of a tightly-coupled INS/GPS integrated scheme by tuning the measurement noise matrix R adaptively. The idea of AKF is based on the maximum likelihood criterion for choosing the most appropriate weight and thus the Kalman gain factors. The conventional EKF implementation suffers uncertain results while the update measurement noise matrix R and/or the process noise matrix Q does not meet the case. 3. THE IMPLEMENTAION OF AKF SCHEMES The AKF can be implemented by Multi model adaptive estimation (MMAE) and Innovation-based adaptive estimation (IAE), respectively. Those methods need to calculate the innovation sequence, which is obtained by the difference between real measurement received by the filter and predicted value. At the current epoch &, not only the new measurement but the predicted value provides the new information. Hence, the innovation sequence represents the information satisfy the new measurement and considered as the most relevant source of the adaptive filter. See Genin (1970), Kailath (1972) and Kailath (1981) for more details. The primary advantage of AKF is that the filter has less relationship with the priori statistical information because the R and/or Q matrices vary with time. According to Schwarz and Mohamed (1999), the IAE scheme is more efficient than MMAE scheme. Therefore, the IAE scheme is chosen in this study. The innovation sequence is used to derive the measurement weights through the covariance matrix R in this study. In the IAE method implemented in study, the covariance matrix R is adapted when measurements update with time. A window based approach is implemented to update the quality of GPS pseudo-range measurements by adaptively

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