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

>, too. The raw GPS when less enefit in a vhere the bstruction tecture the EKF h serious ements. In the quality 's place in f reflected > Adaptive ly-coupled nent noise maximum ate weight onal EKF 1e update > matrix Q MES . adaptive estimation culate the difference predicted asurement jn. Hence, satisfy the t source of 1972) and se of AKF statistical | time. scheme is .E scheme is used to 1ce matrix study, the pdate with update the adaptively replace the measurement weights through the latest estimated covariance matrices R. Figure 4 depicts the implementation of IAE procedure. Ze Compute C, bod Compute R | Kalman Filter Loop Figure 4. IAE computing procedure In the IAE approach, the measurement covariance matrix R and system noise covariance matrix Q are tuned by measurements of different time. The study focuses on the influence of the qualities of measurements, so only the measurement covariance matrix R is variable. The formulations of AKF are shown below (R-only) (Schwarz and Mohamed, 1999). Vp Zí 7 Hu (1) ^ | 7 C.=— > yvy @) Vk 2? J R, 2C, HP HT (3) Where V, represents the innovation sequence and C. is the covariance of innovation sequence at epoch À. jy is the first epoch of estimation window, and it would be calculated by Jo — k — N 1 and N is the size of window. The integrated algorithm in this study is applied for land vehicle navigation. Therefore, the velocity of land vehicle navigation constraints is derived assuming that the vehicle does not slip, which is a close representation for travel in a constant direction. A second assumption is that the vehicle stays on the ground, i.e. it does not jump of the ground. If both assumptions are true, non-holonomic constraints (NHC) are defined as the fact that unless the vehicle jumps off the ground or slides on the ground, the velocity of the vehicle in the plane perpendicular to the forward direction is almost zero (Sukkarieh, 2000; Nassar et al., 2006; Godha, 2006). Figure 5 shows the scenario of non- holonomic constraints in the b-frame. Therefore, two constraints can be considered as measurement updates to the Kalman filtering navigation: b v, e 0 (4) b v, &0 Voc Figure 5. The two non-holonomic constraints in the b-frame The body frame velocity can be given as: $26" (Cw (5) Perturbing Equation 5 expresses: voa rid - E" yc; p. o" + dv) = chu -EÜ"ys"..", (0) Collecting terms to the first order, the velocity error dynamics can be written as: on’ = ca + CE = C^óy" il C^(v"x) e" (7) 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 Then the measurement matrix can be given as: Zr SLY (8) mue qe Ciz Car 32, 7 DC22 SEC, *DÉID 0 3o C13 0€) Cg imr pCog X vgCSa VDE 053 9x3 0 4 (9) 053 053 0 0 2x17 Cy: the (i, j) elements from the DCM C7 In general, the velocity output of the inertial navigation mechanization V" can be transformed to the body frame velocity y? by the attitude error dynamics DCM C T . And the NHC . : Z, is used as the measurements in the Kalman filter. The estimated errors will be fed back to the mechanization then. Finally, the implementation of the Kalman filters with non- holonomic constraints in INS-based tightly-coupled integrated systems can be illustrated as Figure 6. Figure 6. INS-based tightly-coupled integrated systems with NHC 4. RESULTS AND ANALYSIS To validate the performance of proposed algorithm, the field scenario of the land vehicle was conducted in the downtown area of Tainan. Reference and test systems were installed on the test vehicle. The geodetic GPS receiver with double frequency board and the low-cost GPS receiver with single frequency board were applied in the field scenario. In the case of INSs, the two tactical grade INSs were applied. 4.1 Test Instrument Table 1 and Table 2 show the specifications of the GPS receivers and INSs used in the field scenario. Table 1. The specifications of the GPS receivers NovAtel OEMV-3 | U-blox AEK-4T (Geodetic) (Low-cost) ; Channels 14 L1,14 L2,6 L5 16 LI Receiver C/A code, P code, Type Data type Carrier Phase C/A Code Accuracy SPP (m) L11.8 Li+E2:1.5 3.0 (RMS) DGPS (m) 0.45 2.4 Table 2. The specifications of the INSs Type of IMU Grade Gyro Drift | Acc. Drift SPAN-CPT Tactical 1 deg/hr 0.75 C-MIGITS III | Tactical 3 deg/hr 0.2

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