Performance Evaluation of Optech's ALTM 3100: Study on Geo-Referencing Accuracy
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1 Performance Evaluation of Optech's ALTM 3100: Study on Geo-Referencing Accuracy R. Valerie Ussyshkin, Brent Smith, Artur Fidera, Optech Incorporated BIOGRAPHIES Dr. R. Valerie Ussyshkin obtained a Ph.D. in Physics from Bar-Ilan University in She has been with Optech since 2000 as a Project/System Scientist in the Space and Atmospheric Division and the Terrestrial Survey Division. She is working extensively in the area of airborne and spaceborne lidar technology. Dr. Brent Smith is a senior project manager with broad experience in managing the design and construction of laser-based ranging, imaging and atmospheric monitoring systems. He was project manager of Optech's ALTM 1025 program, leading the development of this 25-kHz laser airborne terrain mapping system. Since then, he has been extensively involved in every ALTM model leading up to the latest ALTM Mr. Artur Fidera is a Data Processor in the Terrestrial Survey Division who specializes in ALTM data processing. He has core expertise in both geomatics and surveying. ABSTRACT Airborne laser scanning is used to generate topographic maps with accuracies on the decimeter level. Recent studies of the Optech ALTM 3100 Airborne Laser Terrain Mapper system demonstrate that this instrument is capable of relative accuracies on the sub-decimeter level. The limiting factors in obtaining absolute sub-decimeter accuracies are the GPS and INS systems that are required to provide absolute position and orientation during flight. This paper presents a summary of the vertical assessment results for the ALTM 3100, a discussion of the contributions to overall error in this instrument, and presents a new study on the geo-positioning system to be performed in the coming months INTRODUCTION Over the past decade, airborne lidar technology has emerged as the premier surveying and mapping tool of choice. The advantages of fast operation and low cost have provided the lift in airborne lidar s ascent to the top. Early system specifications had low data collection rates (a few khz) and less accurate subsystems compared to their modern day counterparts. Airborne lidar systems have rapidly improved over the years, driven by technological advances in several subsystems. The introduction of new technologies, an increase in the laser pulse repetition frequencies (PRF), the use of more capable scanners, and a new generation of position orientation systems (POS) has enabled sub-decimeter relative levels. Optech s Airborne Laser Terrain Mapper (ALTM) is rapidly evolving. Despite substantial technological advances in newly developed ALTM subsystems, the overall specifications have not changed. This paper reports on our efforts to continue re-evaluation of the ALTM ground point. We will start with the general overview of the sources of error in airborne lidar scanning systems. Then, the new study on ALTM performance evaluation will be outlined. The results of the first part of this study, that assessed the vertical of the ALTM, will be briefly overviewed and presented here. Then, the performance of the GPS/INS subsystem will be discussed, and some preliminary results of the study of geo-positioning data will be presented. Figure 1: Error budget of an airborne lidar system SOURCES OF ERROR The overall airborne lidar system performance is determined by the performance of two major subsystems: the lidar scanner and the position and orientation (POS) system. The total error budget contributing to ground point of lidar data is usually divided between: 1089
2 lidar instrument errors, POS errors, misalignment errors, data processing errors. Each of these individual categories has other errors associated with it (Figure 1) ALTM 3100 PERFORMANCE EVALUATION The ALTM 3100 model was introduced to the market a few years ago. Table 1 lists some of the key specifications derived from preliminary system performance evaluations. Since then, significant modifications to the system hardware, software and firmware have been implemented. The performance of some ALTM subsystems has also been improved. Using the specifications presented in Table 1 as a starting point, a new evaluation of the overall system performance has been initiated. To maintain a systematic approach, the study was preliminary structured as follows: Rangefinder performance evaluation Scanner performance evaluation GPS/INS performance evaluation Boresight calibration: How well can we calibrate the system How stable is the calibration with respect to temperature, vibration, etc. How reproducible are the calibration parameters. Characterize contribution from the other errors. The end goal of this study is the assessment of the vertical and horizontal (planimetric) of ALTM system. Then, another approach that considers contribution of the errors from various subsystems to the vertical and horizontal could also be adopted. 1 As an initial attempt to characterize the lidar instrument errors influencing elevation data, ALTM vertical has been assessed. 2 A brief overview of this study is presented in the following section VERTICAL ACCURACY ASSESSMENT Table 1: ALTM 3100 performance specifications (shaded areas are of importance to this discussion) Specification Operating altitude Horizontal Elevation Intensity capture Scan frequency Scan angle Scanner product Roll compensation Position Orientation System Laser pulse repetition frequency (PRF) Beam divergence Eye safe range Value m nominal 1/3000 x altitude; 1-σ < m; 1-σ < m; 1-σ < m; 1-σ 12-bit dynamic range for each measurement Variable; 0-70 Hz Variable from 0 to ±25, in increments of ±1º Scan Angle x Scan Frequency Hz update rate (Scan angle + Roll Comp. Angle = FOV, i.e. ±25º allows ±5º compensation) Applanix/Optech custom AV510 POS including internal 12 channel dual frequency 10 Hz GPS receiver 33 khz (maximum AGL 3.5 km) 50 khz (maximum AGL 2.5 km) 70 khz (maximum AGL 1.7 km) 100 khz (maximum AGL 1.1 km) Dual 0.3 mrad (1/e) or 0.8 mrad (1/e)* mrad (wide beam, unaided) mrad (narrow beam, unaided) mrad (wide beam, aided or narrow unaided profiling) mrad (narrow beam, aided) The absolute positional error in a lidar sounding depends on bias and random errors from a number of subsystems. In the initial assessment of the ALTM 3100 s vertical, we removed the bias errors and looked only at the random errors in the vertical position. Gross bias errors were removed by calibrating the ALTM systems so that bias errors were minimized. Additional bias errors such as GPS offsets were removed by block adjustments to the data. Using a control surface approach, residual biases were also removed from the data. To minimize coupling between horizontal and vertical positional errors, the study was done over flat terrain. Using this approach, the standard deviation of the elevation data was the basic parameter used in this study. 2 Figure 2: 1-σ and 2-σ standard deviation averaged over three flights per system. Three ALTM 3100s were operated at the model s four PRFs: 33 khz, 50 khz, 70 khz, and 100 khz. The systems were flown at 1100 m, 1550 m, 2200 m, and 1090
3 3100m above ground level (AGL). 1-σ and 2-σ standard deviation of the elevation data, collected during at least three flights for each system, were computed through the workflow described in the study. 2 Figure 2 summarizes the results of this work. Comparing these results with the performance specs shown in Table 1, the 1-σ accuracies quoted by Optech few years ago are decidedly conservative at all altitudes and repetition rates. We have demonstrated that technically improved subsystems can lower noise levels present in the data. However, it is important to keep in mind that we are only observing the standard deviations of the overall data, and not true that takes GPS bias errors into account. Therefore, the reported accuracies can only be achieved by applying a block adjustment to the entire data set that coincides with the assessed vertical error produced by systematic GPS errors. This analysis demonstrated that the ALTM 3100 is capable of relative accuracies on the sub-decimeter level. The limiting factor in obtaining sub-decimeter is therefore the POS subsystem performance. In the next section, we outline a new study on the performance of the GPS/INS system used in the ALTM 3100 to provide its absolute position and orientation in flight GPS/INS SYSTEM PERFORMANCE Before we go into details about the GPS/INS study, it is important that we first discuss the technical specifications of the ALTM GPS/INS subsystem, and the ALTM postprocessing workflow APPLANIX POS/AV SYSTEM As shown in Table 1, Optech is using the Applanix POS/AV system, which is a direct geo-referencing system providing differential GPS measurements integrated with an Inertial Measurement Unit (IMU). The Applanix POS system has four main components 3 : 1. Differential dual-frequency GPS receiver (DGPS) 2. Integrated Inertial Measurement Unit (IMU) 3. Computer system real-time control (PCS) 4. Post-processing software suite (POSPac) The heart of the system is the integrated Inertial Navigation Software (INS), which is implemented in realtime by PCS, and in post-processing by POSPac. With POSPac, the GPS measurements are blended with the IMU output. The blended data produces a position and orientation solution that retains dynamic of the inertial navigation system, and has absolute of GPS. 4 Table 2: POS/AV 510 V5 post-processed absolute (1-σ RMS) Position Roll & Pitch (deg) Heading (deg) Table 3: POS/AV 510 V5 post-processed relative Noise (deg/sqrt(hr)) <0.01 Drift (deg/hr) 0.1 The absolute position of the POS/AV-smoothed position is typically 3-30 cm RMS (POS RMS). The orientation of the POS/AV system is specified as absolute and relative. The absolute is the POS RMS error in the roll, pitch, and heading angles. The relative orientation is a function of the gyro random walk noise and the gyro drift, which are respectively specified as noise and drift parameters. The post-processed position and orientation accuracies of Applanix POS/AV 510 V5 system are presented in Table 2 and Table ALTM POST-PROCESSING WORKFLOW POS/AV is used to measure the position and orientation of the laser reference point (the scanning mirror) at the exact time of the range measurement (the laser shot). During a mission, the POS records the IMU data, GPS data, and the time stamp of each laser shot in one common time base. The POSPac software interpolates the position and orientation data to the exact time of the laser shot. Then, the data is combined with the range measurements, whereby a 3D ground-spot coordinate for the each laser shot is computed. The process of getting the 3D elevation map from the lidar data can be described in the following workflow: 1. Organize raw data into manageable files using the Applanix POSPac extract function, and the REALM (Optech s ALTM processing suite) decode program. 2. Process and optimize GPS data within the Applanix POSPac module. 3. Optimally blend the differential GPS solution with the IMU data to produce a Smoothed Best Estimate of Trajectory (SBET), using the Applanix POSPac module. 4. Import the SBET file into REALM. 5. Define the project, select coordinate systems, identify areas of interest, select calibration files, 1091
4 and enter the laser point computation and output information. 6. Process the data. 7. Run the data through ACalib, Optech s automated calibration application. 8. Visually review and verify the final data for QC purposes using a visualization software tool. 9. Document and organize results METHODOLOGY The data was collected during standard calibration flights of Optech s ALTM 3100 system. The analysis is based on four recently built systems. Each system was tested on three separate occasions to de-correlate data, and to ensure reproducibility of calibration results. Figure 3: Post-processed absolute GPS/INS position (1-σ RMS) for four ALTM3100 systems The GPS/IMU position and orientation data were postprocessed using Applanix s POSPac 4.2 software. The absolute position and orientation parameters of GPS/IMU, RMS errors for northing, easting and height, and roll, pitch and heading, were extracted from the SBET files and averaged over number of flights for each system. The velocity vector data was not used in this study. The estimated errors derived from this analysis will be used to evaluate the influence of the geo-referencing data errors on the ground point of ALTM data PRELIMINARY RESULTS An example of the typical post-processed position RMS data for four ALTM systems is shown in Table 4. Similar data was collected for roll, pitch and heading POS RMS errors. This data is presented in comparison with the performance specifications of POS/AVTM 510 V5 in Figure 3 and Figure 4. Table 4: Post processed position 1-σ RMS data System I II III IV Julian day Northing Easting Height Position Figure 4: Post-processed roll and pitch absolute (1-σ RMS) for four ALTM3100 systems CONCLUSIONS The ALTM 3100 system performance evaluation is still in progress. The results of the vertical analysis indicated that the original quoted performance specifications are conservative. The overall ground point position of ALTM data strongly depends on GPS/INS system performance. The new study on geopositioning data indicates that the postprocessed RMS position error is always <5 cm. However, the orientation data was not very consistent, which requires further investigation and analysis in the coming months ACKNOWLEDGMENTS All data presented in this paper was processed by the Data Processing Team (Terrestrial Division) at Optech Incorporated. All results were verified by the authors of this paper. The authors thank the team that dedicated much of their time to process the data and compile the results. 1092
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