An overview of the laser ranging method of space laser altimeter

Zhou, Hui; Chen, Yu Wei; Hyyppä, Juha; Li, Song

doi:10.1016/j.infrared.2017.09.011

Cited by 27 publications

(17 citation statements)

References 43 publications

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“…, the principle of laser ranging involves obtaining the range based on the flight time of the laser. This work applies the time without correction for any difference between the down range and the return range (Zhou et al., ). The time interval between the transmitted and received laser pulses is determined from the waveform using the following equation:

Δ t = T_{receive} - T_{transmit} .

…”

Section: Methodsmentioning

confidence: 99%

In‐orbit geometric calibration and experimental verification of the ZY3‐02 laser altimeter

Xie

Tang

et al. 2018

The Photogrammetric Record

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ZY3-02 is the first Chinese earth-observation satellite equipped with a laser altimeter, designed to assist stereo-image mapping elevations. Launch vibrations, the space environment and other factors, both expected and unexpected, cause bias in the designed ranging and pointing of the laser altimeter, influencing its height measurement accuracy. This paper proposes an in-orbit geometric calibration model which considers this bias as unknown systematic errors. The unknown parameters were calibrated by the minimum ranging error principle using laser spot geolocation data captured by a ground-based laser detector array. Based on precise orbit and attitude data, the precise geolocation information of the laser footprints could be obtained. Validation experiments show that the elevation precision of the laser altimeter can reach 1 m.

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Δ t = T_{receive} - T_{transmit} .

…”

Section: Methodsmentioning

confidence: 99%

In‐orbit geometric calibration and experimental verification of the ZY3‐02 laser altimeter

Xie

Tang

et al. 2018

The Photogrammetric Record

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“…Airborne large-footprint lidar systems are predominantly composed of a laser, telescope, relay optical system, detector, and signal acquisition and processing subsystem [29]. All signal amplifiers in lidar detector electronic circuits have finite linear dynamic ranges [24].…”

Section: Signal Saturation Processingmentioning

confidence: 99%

Accuracy Verification of Airborne Large-Footprint Lidar based on Terrain Features

Lian

Zhang

et al. 2020

Remote Sensing

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Accuracy verification of airborne large-footprint lidar data is important for proper data application but is difficult when ground-based laser detectors are not available. Therefore, we developed a novel method for lidar accuracy verification based on the broadened echo pulse caused by signal saturation over water. When an aircraft trajectory crosses both water and land, this phenomenon and the change in elevation between land and water surfaces can be used to verify the plane and elevation accuracy of the airborne large-footprint lidar data in conjunction with a digital surface model (DSM). Due to the problem of echo pulse broadening, the center-of-gravity (COG) method was proposed to optimize the processing flow. We conducted a series of experiments on terrain features (i.e., the intersection between water and land) in Xiangxi, Hunan Province, China. Verification results show that the elevation accuracy obtained in our experiments was better than 1 m and the plane accuracy was better than 5 m, which is well within the design requirements. Although this method requires specific terrain conditions for optimum applicability, the results can lead to valuable improvements in the flexibility and quality of lidar data collection.

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“…This is achieved by accurate measurements of the times-offlight of short (few ns) laser pulses. Currently, there exist four commonly adopted methods to measure the times-of-flight: leading-edge detection, waveform processing and analyzing, constant fraction discrimination, and photon-counting; see for details [20]. Given the trajectory and attitude of the spacecraft, pointing alignment of the laser altimeter, and rotational model of the target body, the time-of-flight measurements can be converted to surface coordinates in the body-fixed reference frame of the target body, i.e., the geolocation process.…”

Section: Introductionmentioning

confidence: 99%

Recomputation and Updating of MOLA Geolocation

et al. 2022

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The Mars Orbiter Laser Altimeter (MOLA) Precision Experiment Data Records (PEDR) serve as the geodetic reference of Mars. However, these MOLA footprints were geolocated using outdated auxiliary information that dates back to 2003. In this study, we recompute the MOLA PEDR footprint locations and investigate the impact of the updated spacecraft orbit model and Mars rotational model on MOLA’s geolocation. We observe quasi-exponential increases near the poles of up to 30 m in the recomputation residuals for the nadir profiles. Meanwhile, we demonstrate that limitations exist in the stored MOLA PEDR attitude records, which can shift the footprint up to hundreds of meters laterally and several meters radially. The usage of the Navigation and Ancillary Information Facility (NAIF)-archived attitude information instead can circumvent this issue and avoid the approximation errors due to discrete samplings of the attitude information used in geolocation by the PEDR dataset. These approximation errors can be up to 60 m laterally and 1 m radially amid controlled spacecraft maneuvers. Furthermore, the incorporation of the updated spacecraft orbit and Mars rotational model can shift the MOLA profiles up to 200 m laterally and 0.5 m radially, which are much larger in magnitude than the aforementioned dramatic increases near the poles. However, the shifted locations of the reprocessed profiles are significantly inconsistent with the PEDR profiles after the global cross-over analysis.

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An overview of the laser ranging method of space laser altimeter

Cited by 27 publications

References 43 publications

In‐orbit geometric calibration and experimental verification of the ZY3‐02 laser altimeter

In‐orbit geometric calibration and experimental verification of the ZY3‐02 laser altimeter

Accuracy Verification of Airborne Large-Footprint Lidar based on Terrain Features

Recomputation and Updating of MOLA Geolocation

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