Sung-Hyuck Im

GPS/DR Error Estimation for Autonomous Vehicle Localization

Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.

Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area

Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m.

Pedestrian Safety Road Marking Detection Using LRF Range and Reflectivity

In this paper, a detection method of a pedestrian safety road marking was proposed. The proposed algorithm uses laser range and reflectivity of a range finder (LRF). For a detection of crosswalk marking and stop line, the DFT (Discrete Fourier Transform) of reflectivity and cross-correlation method between the reference replica and the measured reflectivity are used. A speed bump is detected through measuring an altitude difference of two LRFs which have the different tilted angle. Furthermore, we proposed a velocity constrained a detection method of a speed bump. Finally, the proposed methods are tested in on-line, on the pavement of a road. The considered road markings are wholly detected. The localization errors of both road markings are smaller than 0.4 meter.

Effect of Spoofing on Unmanned Aerial Vehicle using Counterfeited GPS Signal

Global Navigation Satellite System (GNSS) including Global Positioning System (GPS) is an important element for navigation of both the military and civil Unmanned Aerial Vehicle (UAV). Contrary to the military UAVs, the civil UAVs use the civil signals which are unencrypted, unauthenticated and predictable. Therefore if the civil signals are counterfeited, the civil UAV’s position can be manipulated and the appropriate movement of the civil UAV to the target point is not achieved. In this paper, spoofing on the autonomous navigation UAV is implemented through field experiments. Although the demanded conditions for appropriate spoofing attack exists, satisfying the conditions is restricted in real environments. So, the Way-point of the UAV is assumed to be known for experiments and assessments. Under the circumstances, GPS spoofing signal is generated based on the Software-based GNSS signal generator. The signal is emitted to the target UAV using the antenna of the spoofer and the effect of the signal is analyzed and evaluated. In conclusion, taking the UAV to the target point is hardly feasible. To implement the spoofing as expectation, the position and guidance system of the UAV has to be known. Additionally, the GPS receiver on the UAV could be checked whether it appropriately tracks the spoofing signal or not. However, the effect of the spoofing signal on the autonomous UAV has been verified and assessed through the experimental results. Spoofing signal affects the navigation system of the UAV so that the UAV goes off course or shows an abnormal operation.

Software-based Real-time GNSS Signal Generation and Processing Using a Graphic Processing Unit (GPU)

A graphic processing unit (GPU) can perform the same calculation on multiple data (SIMD: single instruction multiple data) using hundreds of to thousands of special purpose processors for graphic processing. Thus, high efficiency is expected when GPU is used for the generation and correlation of satellite navigation signals, which perform generation and processing by applying the same calculation procedure to tens of millions of discrete signal samples per second. In this study, the structure of a GPU-based GNSS simulator for the generation and processing of satellite navigation signals was designed, developed, and verified. To verify the developed satellite navigation signal generator, generated signals were applied to the OEM-V3 receiver of Novatel Inc., and the measured values were examined. To verify the satellite navigation signal processor, the performance was examined by collecting and processing actual GNSS intermediate frequency signals. The results of the verification indicated that satellite navigation signals could be generated and processed in real time using two GPUs.

Performance Evaluation of Vector Tracking Loop Based Receiver for GPS Anti-Jamming Environment

In this paper, we represent the implementation and performance analysis of vector tracking loop based GPS receiver for jamming environment. The vector tracking loop navigation performance is compared by simulation with conventional tracking loop. The simulation results shows that vector tracking loop is more robust than conventional tracking loop in jamming environment. The vector tracking loop can gain 2dB in jamming performance capability over a conventional GPS receiver. Also, Anti-jamming performance of INS Doppler aiding and deep integration method are compared.

An Analysis of Spoofing Effects on a GNSS Receiver Using Real-Time GNSS Spoofing Simulator

In this paper, spoofing effects on a GNSS receiver were analyzed. The spoofer (spoofing device) was classified to two categories. One is an active spoofer and the other is a passive spoofer. The active spoofer was considered for analysis. For the analysis of spoofing effects on a GNSS receiver, a real-time GNSS spoofing simulator was developed. The simulator was consisted with two parts which are a baseband signal generation part and a RF up-conversion part. The first GNSS baseband signal was generated according to spoofing parameters such as range, range rate, GNSS navigation data, spoofing to GNSS signal ratio, and etc. The generated baseband signal was up-converted to GNSS L1 band. Then the signal transmitted to a GNSS signal. For a perfect spoofing, a spoofer knew an accurate position and velocity of a spoofing target. But, in real world, that is not nearly possible. Although uncertainty of position and velocity of the target was existed, the spoofer was operated as an efficient jammer.

Performance Improvement of Inertial Navigation System by Using Magnetometer with Vehicle Dynamic Constraints

A navigation algorithm is proposed to increase the inertial navigation performance of a ground vehicle using magnetic measurements and dynamic constraints. The navigation solutions are estimated based on inertial measurements such as acceleration and angular velocity measurements. To improve the inertial navigation performance, a three-axis magnetometer is used to provide the heading angle, and nonholonomic constraints (NHCs) are introduced to increase the correlation between the velocity and the attitude equation. The NHCs provide a velocity feedback to the attitude, which makes the navigation solution more robust. Additionally, an acceleration-based roll and pitch estimation is applied to decrease the drift when the acceleration is within certain boundaries. The magnetometer and NHCs are combined with an extended Kalman filter. An experimental test was conducted to verify the proposed method, and a comprehensive analysis of the performance in terms of the position, velocity, and attitude showed that the navigation performance could be improved by using the magnetometer and NHCs. Moreover, the proposed method could improve the estimation performance for the position, velocity, and attitude without any additional hardware except an inertial sensor and magnetometer. Therefore, this method would be effective for ground vehicles, indoor navigation, mobile robots, vehicle navigation in urban canyons, or navigation in any global navigation satellite system-denied environment.

GNSS Precise Positioning Design for Intelligent Transportation System

In this paper, a structure of precise positioning based on satellite navigation system is proposed. The proposed system is consisted with three parts, range domain filter, navigation filter and position domain filter. The range domain filter generates carrier phase-smoothed-Doppler and Doppler-smoothed-code measurements. And the navigation filter calculates position and velocity using double-differenced code/carrier phase/Doppler measurements. Finally, position domain filter smooth position error, and it means enhancement of positioning performance. The proposed positioning method is evaluated by trajectory analysis using precise map date. As a result, the position error occurred by multipath or cycle slip was reduced and the calculated trajectory was in true lane.

A GNSS Signal Correlation Using Map-based Partial-time Common Intermediate Frequency Removal Method

In this paper, we propose the efficient Doppler removal method using map-based partial-time common intermediate frequency removal technique. In the proposed algorithm, the 2-stage carrier removal process was used. First, the component of common intermediate frequency is removed. Next the component of Doppler was removed with averaging and approximation. For the evaluation of the proposed algorithm, The real-time software GPS L1 C/A-code receiver was implemented. When the proposed algorithms are used, 12 tracking channels with 3 track arm(early, prompt, late) is operated real-time on PC using a Intel Pentium-III 1.0GHz CPU. Also, the requirement of memory was less than 2Mbytes. The real-time software GNSS receiver using the proposed algorithms provides the navigation solution with below 10 meter rms error. Especially, in spited of using the various approximations for implementing the algorithms, the high sensitivity capability (able to track the weak signal with -159dBm) was achieved.