Center for Mapping. He received an MS in Electrical Engineering and a Ph.D. in Electrical Enginee... more Center for Mapping. He received an MS in Electrical Engineering and a Ph.D. in Electrical Engineering and Geoinformation Sciences from the Technical University of Budapest, Hungary. His research expertise covers broad areas of 2D/3D signal processing, spatial information systems, high-resolution imaging, surface extraction, modeling, integrating and calibrating of multi-sensor systems, multi-sensor geospatial data acquisition systems, and mobile mapping technology. He is Co-Chairing ISPRS WG II/2 on LiDAR and InSAR Systems and serves as the Assistant Director for the Photogrammetric Application Division of ASPRS. ABSTRACT In the majority of multi-sensor mapping systems, the GPS/INS integration serves as a navigation and georegistration tool, supporting the simultaneously acquired imagery. In a tightly coupled integration architecture, where double difference (DD) GPS carrier phase observations and the IMU (inertial measurement unit) accelerometer and gyroscope data are integrated in...
International Association of Geodesy Symposia, 2007
... technology is the expected next step in traffic monitoring and management, as it can provided... more ... technology is the expected next step in traffic monitoring and management, as it can providedata with large spatial extent and varying temporal resolutions for ... While our earlier publications were focused on the development and performance analysis of the GPS/IMU-based ...
ABSTRACT The Microsoft Kinectâ„¢ sensor has gained popularity in a large number of applications bey... more ABSTRACT The Microsoft Kinectâ„¢ sensor has gained popularity in a large number of applications beyond its intended original design of being a 3D human interface device, including indoor mapping and navigation of pushcart and backpack sensor platforms. Indoor mapping and personal navigation systems are generally based on a multisensory integration model, as currently no sensor itself can provide a robust and accurate solution. To assess the error budget as well as to support the design of such systems, the individual sensor error budgets should be known (estimated). In this paper, a performance analysis of the Kinect sensor is provided based on a series of indoor tests, where sufficient control was available. The main goal of the study is to assess the trajectory reconstruction performance from Kinect imagery only; note that only widely available mainstream imaging tools are used. The investigation aims at estimating and evaluating the total error budget of the 3D mapping process that is based on simultaneously using RGB (2D) and depth (3D) images. The overall error budget is divided into two main parts: (1) the sensor error budget, and (2) the object space error contribution. The first part defines a lower error bound for the 3D object space observation estimation errors, i.e. what can be achieved under ideal conditions. The second part is about the object space dependency, that is the error introduced by the scene content in terms of geometry and texture that can be exploited to identify matching features in the image sequence. While it is difficult to encapsulate the impact of the object space in a rigorous sense, tendencies can be identified based on statistical evaluation of data acquired under typical object space scenarios.
With the Mobile Mapping technology steadily expanding its application market, the accuracy and co... more With the Mobile Mapping technology steadily expanding its application market, the accuracy and continuity of the positioning and attitude delivered by GPS/INS might be a limiting factor to many high-accuracy applications. Thus, a proper selection of an INS sensor as well as GPS receiver might become an issue, even among the high-end instrumentation, primarily due to the different receiver noise levels, and distinct characteristics of the signal processing techniques implemented in GPS hardware by different manufacturers. Medium to high accuracy strapdown systems, such as Litton LN-100 used in this study, combined with a dual frequency differential GPS, allow for reliable almost continuous (256 Hz) trajectory determination. Properly built and calibrated systems can keep the positioning error growth below 10 cm for the horizontal components, and below 20 cm in the vertical direction, even after a 60-second loss of GPS lock, still allowing instantaneous ambiguity resolution after the signal is recovered. During longer gaps, exceeding a few minutes, however, the quality of a free navigation solution decreases quite rapidly, providing positions and attitude estimates that might not meet the accuracy requirements for the most demanding applications. Thus, limiting the gaps in GPS is one of the major issues. Besides the obvious obstruction of the GPS signals, interference and severe multipath are the main reasons why the GPS quality degrades (predominantly in land-based, but also in airborne configurations), especially in urban areas. This ultimately leads to the signal processing performance of the GPS receiver and thus, raises the question which hardware (or more precisely, which receiver hardware and what built-in methods of interference and multipath protection) can cope better with such situations. This paper presents an experimental performance study of high-end dual frequency GPS receivers (Trimble 4000SSE and SSI, Trimble 4700, Topcon/JPS Legacy, Leica 9500 and 399, and Ashtech Z- 12) tested in static, benign conditions on the short and zero baselines, and subsequently, in kinematic scenario. During the kinematic tests, selected receivers were connected to the same antenna and tightly integrated with a single strapdown inertial navigation system, LN100. The difference in the tracking loop implementation, interference and multipath protection in the selected receivers have different effects on the quality and continuity of the GPS/INS data collection. Results from static and kinematic land-based tests, performed mostly in urban areas, are presented in this study.
Center for Mapping. He received an MS in Electrical Engineering and a Ph.D. in Electrical Enginee... more Center for Mapping. He received an MS in Electrical Engineering and a Ph.D. in Electrical Engineering and Geoinformation Sciences from the Technical University of Budapest, Hungary. His research expertise covers broad areas of 2D/3D signal processing, spatial information systems, high-resolution imaging, surface extraction, modeling, integrating and calibrating of multi-sensor systems, multi-sensor geospatial data acquisition systems, and mobile mapping technology. He is Co-Chairing ISPRS WG II/2 on LiDAR and InSAR Systems and serves as the Assistant Director for the Photogrammetric Application Division of ASPRS. ABSTRACT In the majority of multi-sensor mapping systems, the GPS/INS integration serves as a navigation and georegistration tool, supporting the simultaneously acquired imagery. In a tightly coupled integration architecture, where double difference (DD) GPS carrier phase observations and the IMU (inertial measurement unit) accelerometer and gyroscope data are integrated in...
International Association of Geodesy Symposia, 2007
... technology is the expected next step in traffic monitoring and management, as it can provided... more ... technology is the expected next step in traffic monitoring and management, as it can providedata with large spatial extent and varying temporal resolutions for ... While our earlier publications were focused on the development and performance analysis of the GPS/IMU-based ...
ABSTRACT The Microsoft Kinectâ„¢ sensor has gained popularity in a large number of applications bey... more ABSTRACT The Microsoft Kinectâ„¢ sensor has gained popularity in a large number of applications beyond its intended original design of being a 3D human interface device, including indoor mapping and navigation of pushcart and backpack sensor platforms. Indoor mapping and personal navigation systems are generally based on a multisensory integration model, as currently no sensor itself can provide a robust and accurate solution. To assess the error budget as well as to support the design of such systems, the individual sensor error budgets should be known (estimated). In this paper, a performance analysis of the Kinect sensor is provided based on a series of indoor tests, where sufficient control was available. The main goal of the study is to assess the trajectory reconstruction performance from Kinect imagery only; note that only widely available mainstream imaging tools are used. The investigation aims at estimating and evaluating the total error budget of the 3D mapping process that is based on simultaneously using RGB (2D) and depth (3D) images. The overall error budget is divided into two main parts: (1) the sensor error budget, and (2) the object space error contribution. The first part defines a lower error bound for the 3D object space observation estimation errors, i.e. what can be achieved under ideal conditions. The second part is about the object space dependency, that is the error introduced by the scene content in terms of geometry and texture that can be exploited to identify matching features in the image sequence. While it is difficult to encapsulate the impact of the object space in a rigorous sense, tendencies can be identified based on statistical evaluation of data acquired under typical object space scenarios.
With the Mobile Mapping technology steadily expanding its application market, the accuracy and co... more With the Mobile Mapping technology steadily expanding its application market, the accuracy and continuity of the positioning and attitude delivered by GPS/INS might be a limiting factor to many high-accuracy applications. Thus, a proper selection of an INS sensor as well as GPS receiver might become an issue, even among the high-end instrumentation, primarily due to the different receiver noise levels, and distinct characteristics of the signal processing techniques implemented in GPS hardware by different manufacturers. Medium to high accuracy strapdown systems, such as Litton LN-100 used in this study, combined with a dual frequency differential GPS, allow for reliable almost continuous (256 Hz) trajectory determination. Properly built and calibrated systems can keep the positioning error growth below 10 cm for the horizontal components, and below 20 cm in the vertical direction, even after a 60-second loss of GPS lock, still allowing instantaneous ambiguity resolution after the signal is recovered. During longer gaps, exceeding a few minutes, however, the quality of a free navigation solution decreases quite rapidly, providing positions and attitude estimates that might not meet the accuracy requirements for the most demanding applications. Thus, limiting the gaps in GPS is one of the major issues. Besides the obvious obstruction of the GPS signals, interference and severe multipath are the main reasons why the GPS quality degrades (predominantly in land-based, but also in airborne configurations), especially in urban areas. This ultimately leads to the signal processing performance of the GPS receiver and thus, raises the question which hardware (or more precisely, which receiver hardware and what built-in methods of interference and multipath protection) can cope better with such situations. This paper presents an experimental performance study of high-end dual frequency GPS receivers (Trimble 4000SSE and SSI, Trimble 4700, Topcon/JPS Legacy, Leica 9500 and 399, and Ashtech Z- 12) tested in static, benign conditions on the short and zero baselines, and subsequently, in kinematic scenario. During the kinematic tests, selected receivers were connected to the same antenna and tightly integrated with a single strapdown inertial navigation system, LN100. The difference in the tracking loop implementation, interference and multipath protection in the selected receivers have different effects on the quality and continuity of the GPS/INS data collection. Results from static and kinematic land-based tests, performed mostly in urban areas, are presented in this study.
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