Real-time crash avoidance system on crossroads based on 802.11 devices and GPS receivers

By the early 1990’s the Global Positioning System GPS will play a major role in the field of navigation. It will be able to compete with all so far existing radio navigation systems. GPS is a satellite navigation system with a number of unique features, such as world wide coverage, unlimited number of users, 24 hour service, and high accuracy. In its present experimental configuration it has proved a wide verity of application. A user needs no more than a simple antenna and a receiver for 1.5 GHz, a fact that makes GPS attractive for general aviation, as well as for general navigation both on land and at sea. This market can only be opened if GPS receivers cost no more than a high quality car radio. In order to achieve low cost, new ideas have to be introduced to the structuring of receivers.

A novel framework is proposed and demonstrated where satellite visibility viewed from running vehicle is economically and effectively evaluated with such low cost GPS receivers like equipped in automobiles. Our preliminary experiment articulated even economical Ll C/A 1.5GHz GPS receivers can create enough precise database of ground feature blockage, if only two statistical parameters the author proposed are adequately set. Integrating the series of our efforts on this research field, the author also concluded it is feasible to develop an automatic database creation system by the cooperation of the government and the civil with low cost GPS receivers. This blockage database allows us to make feasible real-time handover for running emergency or rescue vehicles in near future’s Land Vehicle Satellite Communication Society.

GPS for low-cost attitude determination: A review of concepts, in-flight experiences, and current developments

Agriculture sector is growing rapidly in the modern era due to rise in global population and shift in trade policies. Replacing human labor with automation of agricultural equipment can alleviate labor shortages and rising costs of farm work to a greater extend. With the inclusion of GPS for navigation, IoT connectivity for remote monitoring and operation, cameras and machine vision systems, the autonomous vehicles will become more capable and self-sufficient over time. However, automation costs need to be reduced to gain a broader acceptance. Tracking a vehicle with low-precision GPS receivers tends to have errors, whereas the inclusion of a high-precision GPS receiver raises the overall cost of the vehicle. In this work, a machine learning-based post-processing techniques have been proposed to enhance position accuracy of a low-cost GPS receiver implemented on an autonomous harvester for monitoring and navigation purpose. The proposed system is integrated with cloud technology where the location coordinates from low-cost GPS receiver get updated to ThingSpeak cloud server using microcontroller. The user can track the position of the vehicle on a smart phone using the designed android app and configure the Geofence around the field for the harvester vehicle to work on. The Geofence alerts the user once the harvester vehicle moves out of the designated field.

Development and performance evaluation of Correntropy Kalman Filter for improved accuracy of GPS position estimation

The performance of low-cost RTK (real-time kinematic) GPS receivers has been compared to a state-of-the-art system as well to each other. Both static and dynamic performances have been compared. The dynamic performance has been evaluated using a vehicle with driving robot on the AstaZero proving ground. The assembly of the low-cost RTK GPS receivers is presented, and the test set-ups described. Besides having a lower data output frequency, two of the low-cost receivers have static and dynamic performance not far from that of the state-of-the-art system.

Within the PROBA-2 microsatellite mission, a miniaturized single-frequency GPS receiver based on commercial-off-the-shelf (COTS) technology is employed for onboard navigation and timing. A rapid electronic fuse protects against destructive single-event latch-ups (SEL) and enables a quasi-continuous receiver operation despite the inherent sensitivity to space radiation. While limited to single-frequency C/A-code tracking with a narrow-band frontend, the receiver is able to provide precision navigation services through processing of raw GPS measurements on ground as well as a built-in real-time navigation system. In both cases, ionospheric path delays are eliminated through a combination of L1 pseudorange and carrier phase measurements, which also offers a factor-of-two noise reduction relative to code-only processing. By comparison with satellite laser ranging (SLR) measurements, a 0.3-m (3D rms) accuracy is demonstrated for the PROBA-2 reduced dynamic orbit determinations using post-processed GPS orbit and clock products. Furthermore, the experimental onboard navigation system is shown to provide real-time position information with a 3D rms accuracy of about 1 m, which notably outperforms the specification of the Standard Positioning Service (SPS). In view of their lower hardware complexity, mass budget and power requirements as well as the reduced interference susceptibility, legacy C/A-code receivers can thus provide an attractive alternative to dual-frequency receivers even for demanding navigation applications in low Earth orbit.

Deliberate jamming of Global Navigation Satellite Systems (GNSS) is becoming more and more a problem in both Navigation Warfare and civilian use of the system. For a better understanding of the effects of a jammer on a GPS receiver we conducted an experiment including a low-cost GPS receiver. This paper discusses the results of this experimental study in which we investigated the influence of radio frequency interference on positioning using a low-cost GPS receiver. The study has been performed with an experimental set-up where a jammer influences a software defined receiver at several distances in an open field. Post-processing the measurements showed that for certain distances the receiver was unable to receive the signals of some satellites with the jammer active. As a result the 95% confidence ellipses enlarged in these situations. Furthermore it was observed that size of the confidence regions depend heavily on the geometry of the satellites, whose signals could be received in the measurements. Results on the pseudorange errors for several jammer to receiver distances are also included in the paper.

In industrial applications is a demand for the highly reliable and synchronous distributed systems. The problem is that in those systems the nodes maintain their own time using local clocks. This behavior can be suppressed by synchronization of the individual nodes. It is more effective to use GPS for synchronization in large distributed systems. This paper deals with evaluation of reachable accuracy of synchronization within industrial distributed system using low-cost GPS receivers. Results of measurements using the uBlox LEA-6T GPS Receiver confirm achievable accuracy better than 15 ns in terms of an RMS value.

The position of mobile devices is determined by Real Time Differential Global Positioning System (RTDGPS). This system is composed of fixed and mobile station. The accuracy of this system depends on the speed of updating the correction data. Yet, this system often faces the problem of the reference GPS receiver’s signal cut off and internal or non- internal delays which increase the latency time and decrease the updating speed. The prediction models are used to compensate these delays. In this paper, the Particle Swarm Optimization Least Square Wavelet Support Vector Machine (PSO-LSWSVM) is used for predicting the DGPS correction. An experimental setup is designed in order to carry out the operations of reference and user stations. Low-cost receivers were used in both stations. The accuracy of PSO-LSWSVM was evaluated through various simulations and experimental. The practical tests showed that the accuracy of the designed RTDGPS is 0.42 m with PSO-LSWSVM and is equal to 0.73 m without it. In comparing with other method that recently is introduced; it has a higher positioning accuracy.

Knowing vehicle sideslip angle accurately is critical for active safety systems such as Electronic Stability Control (ESC). Vehicle sideslip angle can be measured through optical speed sensors, or dual-antenna GPS. These measurement systems are costly (∼$5k to $100k), which prohibits wide adoption of such systems. This paper demonstrates that the vehicle sideslip angle can be estimated in real-time by using two low-cost single-antenna GPS receivers. Fast sampled signals from an Inertial Measurement Unit (IMU) compensate for the slow update rate of the GPS receivers through an Extended Kalman Filter (EKF). Bias errors of the IMU measurements are estimated through an EKF to improve the sideslip estimation accuracy. A key challenge of the proposed method lies in the synchronization of the two GPS receivers, which is achieved through an extrapolated update method. Analysis reveals that the estimation accuracy of the proposed method relies mainly on vehicle yaw rate and longitudinal velocity. Experimental results confirm the feasibility of the proposed method.

<h3>Abstract</h3> This paper describes a novel approach for reducing the kinematic position and time errors on a GPS receiver in low Earth orbit. For dual-frequency GPS receivers, point solution errors are dominated by signal-in-space ranging errors, which introduce sharp discontinuities in the position and time estimates when GPS visibility changes. These discontinuities may be calculated and removed, greatly reducing the peaks of the errors, at the expense of introducing a slowly varying bias, which is estimated and removed. The paper gives a detailed description of the algorithm and illustrates its use on a GPS receiver using historical ephemerides. To demonstrate real-world efficacy, GRACE-FO observations are processed using the proposed approach. Real-time results show the reduction of the time error standard deviation by 16% to 1.9ns and the reduction of the 3D RMS error by 17% to 1.06m. Maximum real-time errors are reduced 26% and 32%, respectively. Delayed processing offers greater reductions of errors, near 40%.

Navigation using low cost inertial unit (IMU-MEMS) and GPS receiver with application of sigma-point Kalman filter

The development of Smart Cities aims to transform city infrastructures and services through the use of information and communication technologies. One aspect of Smart City applications is the demand for more efficient and safe transportation systems. Specifically, road anomalies are some of the challenges that contribute to the increase in vehicle damage and decrease in driver safety. In this paper, we propose a road surface condition monitoring system that utilizes low cost MEMS acceleration sensors and GPS receivers within a tablet to detect and localize road surface anomalies. Several types of road information data were collected, analyzed, and processed using statistical and time domain analysis for feature extraction of the various events. We also propose a multi-level decision-tree classifier to precisely distinguish between the events. In addition, the use of the tablet sensors to localize the monitored events is discussed.

In this paper, an integrated navigation system based on MEMS-IMU/GPS is implemented through optimization of GPS information processing and Kalman filter algorithm. Low-cost IMU and GPS receivers are used with STEM32 as the core of information processing. An improved speed/position combination is adopted in this paper. Test results are presented showing the performance of the integrated MEMS GPS/inertial navigation system: This measure improves aircraft navigation accuracy and corrects the divergence more quickly. This allows integration with less errors characteristic, which is more suitable for aircrafts with low-cost, low-power, lightweight GPS chip receivers and navigation sensors.