Abstract
Abstract. Improving sensor performance, combined with better affordability, provides better object space observability, resulting in new applications. Remote sensing systems are primarily concerned with acquiring data of the static components of our environment, such as the topographic surface of the earth, transportation infrastructure, city models, etc. Observing the dynamic component of the object space is still rather rare in the geospatial application field; vehicle extraction and traffic flow monitoring are a few examples of using remote sensing to detect and model moving objects. Deploying a network of inexpensive LiDAR sensors along taxiways and runways can provide both geometrically and temporally rich geospatial data that aircraft body can be extracted from the point cloud, and then, based on consecutive point clouds motion parameters can be estimated. Acquiring accurate aircraft trajectory data is essential to improve aviation safety at airports. This paper reports about the initial experiences obtained by using a network of four Velodyne VLP- 16 sensors to acquire data along a runway segment.
Highlights
Safety in air and land are important in commercial aviation
The double-blind peer-review was conducted on the basis of the full paper. doi:10.5194/isprsannals-III-1-159-2016
Since the time information is critical for any data fusion, such as estimating the velocity from the point cloud, the scanner receives navigation messages (NMEA) and the 1PPS (Pulse Per Second) timing signal from a GPS receiver via the scanner interface box
Summary
Safety in air and land are important in commercial aviation. A less known fact is that a large number of accidents, including fatalities, happen at airports where aircrafts collide with each other on the ground. Aircrafts, equipped with sophisticated navigation systems based on GPS and IMU sensors, have accurate position and attitude data onboard, but they do not share them with airport management and aviation authorities. Accurate aircraft trajectory data for all aircraft motion at an airport could provide essential information for many purposes. Remote sensing technologies offer a simple, yet reliable way to acquire information of aircraft motion at airports. Another study by FAA/Boeing investigated the 747s’ centerline deviations at JFK and ANC airports (Scholz, 2003a and 2003b) They used laser diodes at two locations to measure the location of the nose and main gears. In Koppanyi and Toth (2015), the feature extraction and parameter estimation methods are introduced, here experiences using a multisensory configuration are reported The double-blind peer-review was conducted on the basis of the full paper
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