On-line Vehicle Motion Estimation from Visual Terrain Information Part II: Ground Velocity and Position Estimation

Bresler, Yoram; Merhav, S. J.

doi:10.1109/taes.1986.310726

Cited by 29 publications

(9 citation statements)

References 2 publications

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“…The efficiency of this temporal redundancy removal depends on the efficiency and accuracy of the motion estimation. There are two classes of motion estimation methods, block matching algorithms (BMA) [2], [3] and pel-recursive algorithms (PRA) [4]. A PRA estimates motion on a pixel-by-pixel basis, whereas a BMA estimates motion on a block-by-block basis.…”

Section: Fast Algorithms For the Estimation Of Motion Vectorsmentioning

confidence: 99%

Hybrid estimation of navigation parameters from aerial image sequence

Sim

Jeong

Lee

et al. 1999

IEEE Trans. on Image Process.

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Abstract-This work presents a hybrid method for navigation parameter estimation using sequential aerial images, where navigation parameters represent the position and velocity information of an aircraft for autonomous navigation. The proposed hybrid system is composed of two parts: relative position estimation and absolute position estimation. Computer simulation with two different sets of real aerial image sequences shows the effectiveness of the proposed hybrid parameter estimation algorithm.

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Section: Fast Algorithms For the Estimation Of Motion Vectorsmentioning

confidence: 99%

Hybrid estimation of navigation parameters from aerial image sequence

Sim

Jeong

Lee

et al. 1999

IEEE Trans. on Image Process.

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“…So far, several navigation parameter extraction techniques, including the inertial navigation system (INS) [2], terrain contour matching (TERCOM) [3,4], and global positioning system (GPS) [5], have been proposed. In the INS, the current position is determined by accumulating displacement, which is estimated using the parameters obtained from the gyroscope and velocity meter.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Implementation of the Relative Position Estimation Algorithm Using the Aerial Image Sequence

et al. 2002

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“…For previous related work in this area, see [1][2][3][4] and the references therein. References [1,2] describe a solution to the problem of estimating the ground velocity and position of an aircraft based on visual terrain information, whereas [3,4] focus on the use of GPS and vision based systems for aircraft navigation during night landing.…”

Section: Introductionmentioning

confidence: 99%

“…References [1,2] describe a solution to the problem of estimating the ground velocity and position of an aircraft based on visual terrain information, whereas [3,4] focus on the use of GPS and vision based systems for aircraft navigation during night landing. Both papers tackle the problem of navigation system design in the context of extended Kalman filters.…”

Section: Introductionmentioning

confidence: 99%

Application of nonlinear filtering to navigation system design using passive sensors

Kaminer

Kang²,

Yakimenko³

et al. 2001

IEEE Trans. Aerosp. Electron. Syst.

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The problem of navigation system design for autonomous aircraft landing is addressed. New nonlinear filter structures are introduced to estimate the position and velocity of an aircraft with respect to a possibly moving landing site, such as a naval vessel, based on measurements provided by airborne vision and inertial sensors. By exploring the geometry of the navigation problem, the navigation filter dynamics are cast in the framework of linear parametrically varying systems (LPVs). Using this set-up, filter performance and stability are studied in an H 1 setting by resorting to the theory of linear matrix inequalities (LMIs). The design of nonlinear, regionally stable filters to meet adequate H 1 performance measures is thus converted into that of determining the feasibility of a related set of LMIs and finding a solution to them, if it exists. This is done by using widely available numerical tools that borrow from convex optimization techniques. The mathematical framework that is required for integrated vision/inertial navigation system design is developed and a design example for an air vehicle landing on an aircraft carrier is detailed.

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On-line Vehicle Motion Estimation from Visual Terrain Information Part II: Ground Velocity and Position Estimation

Cited by 29 publications

References 2 publications

Hybrid estimation of navigation parameters from aerial image sequence

Hybrid estimation of navigation parameters from aerial image sequence

Real-Time Implementation of the Relative Position Estimation Algorithm Using the Aerial Image Sequence

Application of nonlinear filtering to navigation system design using passive sensors

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