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With recent advances of lidar technology, the accuracy potential of lidar data has significantly improved. State-ofthe-art lidar systems can achieve 2 to 3 cm ranging accuracy under ideal conditions, which is the accuracy level required by engineering scale mapping. However, this is also the accuracy range that cannot be realized by routine navigation-based direct sensor platform orientation. Furthermore, lidar systems are highly integrated multi-sensor systems, and the various components, as well as their spatial relationships, introduce different errors that can degrade the lidar data accuracy. Even after careful system calibration, including individual sensor calibration and sensors intra-calibration, certain errors in the collected data can still be present. These errors are usually dominated by navigation errors and cannot be totally eliminated without introducing absolute control information into the lidar data. Therefore, to support applications that require extremely high, engineering scale mapping accuracy, such as transportation corridor mapping, we propose the use of lidar-specific ground targets. Simulations were performed to determine the most advantageous lidar target design and targets were fabricated based upon the simulation results. To investigate the potential of using control targets for lidar data refinement, test flights were carried out with different flight parameters and target distributions. This paper provides a description of the optimal lidar target design, the target identification algorithm, and a detailed performance analysis, including the investigation of the achievable lidar data accuracy improvement using lidar-specific ground control targets in the case of various target distributions and flight parameters.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints-eprint.ncl.ac.uk

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INTRODUCTIONThe primary objective of a mobile mapping system (MMS) is to provide automatic acquisition of directly oriented (georeferenced) digital imagery for mapping and geographic information system (GIS) data collection. The direct georeferencing is most commonly facilitated by the integration of differential GPS (DGPS) and inertial navigation systems (INS), providing nearly continuous (up to 256 Hz) positioning and attitude information of the imaging sensor(s). The navigation data can be processed in near real time or in postmission mode to determine the best estimates of the image exterior orientation. Directly oriented images are then used in photogrammetric processing to extract the feature data, together with their positional information. In the past 10 years, MMSs have evolved toward multisensor and multitasking systems, comprising four primary modules: (1) the control module, (2) the positioning (georeferencing) module, (3) the imaging module, and (4) the data postprocessing module. The modular design creates a system capable of handling numerous concurrent operations in real time and in postprocessing.The MMS presented in this paper is designed for high-accuracy, near-real-time mapping of highway center and edge lines [1]; the system development is currently supported by the Ohio Department of Transportation. The positioning module of this system is based on a tight integration of dual-frequency DGPS carrier phases and raw inertial measurement unit (IMU) data provided by a medium-accuracy, high-reliability strapdown Litton LN-100 INS. The LN-100 is based on a Zero-lock TM Laser Gyro (ZLG TM ) and A-4 accelerometer triad (0.8 nmi/h circular error probable [CEP], gyro bias 0.003 deg/h, accelerometer bias 25 g). An optimal 21-state centralized Kalman filter estimates errors in position, velocity, and attitude, as well as in the inertial and GPS measurements. Under favorable GPS constellations (minimum of 5 -6 satellites) and short to medium baselines, the estimated standard deviations are at the level of 2 -3 cm for position coordinates, and 10 arcsec and 10 -20 arcsec for attitude and heading components, respectively.As a land-based MMS, the system operates primarily in urban environments, where frequent losses of GPS signal lock occur. To prevent major degradation in navigation accuracy and to support ambiguity resolution after GPS signal reacquisition, the loss-of-lock events must be controlled in real time. The MMS control module tracks the duration of the loss of lock (or extended partial satellite blockage) and, based on empirical knowledge of the positioning error growth, provides a warning to the operator that a ZUPT (zero velocity update) is needed (see Figure 1). This empirical information is derived from the system calibration and testing, and facilitates a reference input to the control system. This paper presents the calibration results for the static INS used to derive the empirical information for the system's controls, including observability characteristics. Special emphasis is placed on...

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