Application of laser range scanner based terrain referenced navigation systems for aircraft guidance

Haag, Maarten Uijt de; Vadlamani, A.; Campbell, Jacob; Dickman, Jeff

doi:10.1109/delta.2006.15

Cited by 9 publications

(2 citation statements)

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“…The size of RDEM was 256 256 × , and the size of SDEM was from 16 16 × to 50 50 × . The SDEM were acquired according to simulating model of the I maging laser radar in [1][2][3], and the detailed simulation steps were as follows: 1) Generated the irregular range image by simulating the process of laser radar imaging. 2) Recovered the irregular DEM from the irregular range image.…”

Section: Data Acquisition For Experimentsmentioning

confidence: 99%

“…But if a mismatched position was employed, the error of the navigation system would be evidently increased, which was hardly acceptable. Compared with traditional terrain contour matching algorithm (TEMCOM), which based on radio radar and 1D terrain, 3D terrain matching based on the imaging laser radar had higher accuracy and could be applies to more cases [1][2][3]. Many terrain matching algorithms had been put forward in the recent years.…”

Section: Introductionmentioning

confidence: 99%

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A novel 3D terrain matching algorithm based on image laser radar

Gong

Cheng

et al. 2008

2008 7th World Congress on Intelligent Control and Automation

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The imaging laser radar was an ideal imaging sensor to get the high precision 3D terrain for Terrain aided navigation (TAN). For the application, decreasing the mismatching rate was very important. In this paper, the measurement model of imaging laser radar was introduced and a novel 3D terrain matching algorithm with low mismatching rate was presented. According to the theory of function orthogonal decomposition, a terrain orthogonal decomposition feature vector (TODFV), composed of the orthogonal decomposition coefficients of the digital elevation map (DEM), was employed to represent the features of the terrain. Then TODFV was used to generate an interim matching position vector (IMPV). The IMPV were utilized to do real-time confidence analysis to improve the matching confidence, and were fused to give the final matching at the last. The algorithm could effectively decrease the mismatching rate of terrain matching algorithm, and improved the reliability of TAN. Experiments showed that the algorithm was effective and robust.Index Terms -terrain matching, feature vector, image laser radar.

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Section: Data Acquisition For Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A novel 3D terrain matching algorithm based on image laser radar

Gong

Cheng

et al. 2008

2008 7th World Congress on Intelligent Control and Automation

View full text Add to dashboard Cite

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Terrain‐referenced navigation using a steerable‐laser measurement sensor

Carroll

Canciani

2021

Navigation

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The benefits of GNSS have created dependencies on navigation in modern day aviation systems. Many of these systems operate with no backup navigation source. This makes the capabilities supported by precise navigation vulnerable. This paper investigates a contemporary approach to terrain‐referenced navigation (TRN), used to preserve an aircraft's navigation solution during periods of GNSS denial. Traditionally, TRN has been accomplished using a single measurement sensor pointed nadir to an aircraft. Although shown to be effective, this approach limits the achievable navigation accuracy by restricting the measurable terrain gradients to those below an aircraft. This paper explores an alternative approach to TRN that maximizes navigation information through optimal steering of a gimbaled laser. A Cramér‐Rao lower bound analysis as well as a high‐fidelity simulation establishes the utility of optimal steering while employing TRN. This original approach to TRN shows the order of magnitude improvements in navigation performance over existing methods.

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