Joon Wayn Cheong

GPS/WiFi Real-Time Positioning Device: An Initial Outcome

The Global Positioning System ( GPS) has a typical outdoor positioning accuracy of up to 15m for civilian users. Thus, it has become a viable method for civilian to carry out coarse positioning. However, it has its shortcomings; it is available only in indoors with a clear view of the sky. Since WiFi has become another proven positioning technology that is capable of performing positioning in indoor environments and urban canyons, it is desirable to combine both of these technologies for ubiquitous positioning. Therefore, by means of integrating GPS positioning with a WiFi positioning system, indoor and outdoor positioning may be performed using only one device. The device can be implemented using FPGA embedded systems technology that allows easy reconfi guration of the device. Such a combination allows GPS and WiFi positioning technology to transition seamlessly.

An ultra-wide bandwidth-based range/GPS tight integration approach for relative positioning in vehicular ad hoc networks

Relative position awareness is a vital premise for the implementation of emerging intelligent transportation systems, such as collision warning. However, commercial global navigation satellite systems (GNSS) receivers do not satisfy the requirements of these applications. Fortunately, cooperative positioning (CP) techniques, through sharing the GNSS measurements between vehicles, can improve the performance of relative positioning in a vehicular ad hoc network (VANET). In this paper, while assuming there are no obstacles between vehicles, a new enhanced tightly coupled CP technique is presented by adding ultra-wide bandwidth (UWB)-based inter-vehicular range measurements. In the proposed CP method, each vehicle fuses the GPS measurements and the inter-vehicular range measurements. Based on analytical and experimental results, in the full GPS coverage environment, the new tight integration CP method outperforms the INS-aided tight CP method, tight CP method, and DGPS by 11%, 15%, and 24%, respectively; in the GPS outage scenario, the performance improvement achieves 60%, 65%, and 73%, respectively.

A DSRC Doppler/IMU/GNSS Tightly-coupled Cooperative Positioning Method for Relative Positioning in VANETs

Relative position awareness is a vital premise for the implementation of emerging intelligent transportation systems. However, commercial Global Satellite Navigation Systems (GNSS) receivers do not satisfy the requirements of these applications. Fortunately, Cooperative Positioning (CP) systems, based on inter-vehicle communications, have improved performance of relative positioning in a Vehicular Ad Hoc Network (VANET). CP techniques rely primarily on measurements from the Global Positioning System (GPS) to deliver measurements or positions that describe the location of individual vehicles. In urban environments, the reduced quality or complete unavailability of GPS measurements challenges the effectiveness of any CP algorithm. In this paper, a new enhanced tightly–coupled CP technique is presented by adding the measurements from low-cost inertial sensors and the Doppler shift of the carrier of Dedicated Short-Range Communications (DSRC) signals. In the enhanced CP method proposed here, vehicles communicate their Inertial Measurement Unit (IMU) data and GPS measurements. Each vehicle fuses the GPS measurements and IMU data and the inter-node range-rates based on the Doppler shift of the carrier of DSRC signals. Based on analytical and experimental results, in a full GPS coverage environment, the new tight integration CP outperforms tight CP with Inertial Navigation System (INS), tight CP and differential GPS by at least by 6%, 15%, and 28%, respectively. In a GPS outage, the performance improvement can be up to 60%, 55%, and 66% respectively.

Improvement to Multi-resolution Collective Detection in GNSS Receivers

Collective detection is a promising approach to positioning in a weak signal environment, in which the navigation solution is directly obtained by acquisition search in a multidimensional position and common clock bias uncertainty space. By combining the correlation values from multiple satellites and fully utilizing the coherence between them, the detectable C/N0 of individual satellites can be lowered. However, the lack of a computationally efficient optimization algorithm due to high dimensionality and complexity has hindered its application. A multi-resolution collective detection is therefore proposed to be a coarse-to-fine searching approach to solve for the position and common clock bias estimation. Although it reduces the computation time of collective detection, there is a gap in the efficiency study, which is the contribution of this research. The features of different levels of search in a multi-resolution algorithm are investigated. For a coarse search with large horizontal position step size, a smaller common clock bias step size is proposed instead of an averaging correlogram to reduce computation complexity as well as to obtain high time resolution. For the fine search with small horizontal space step size, a 3-D Dichotomous searching scheme is designed and applied to reduce the number of searching grids. Computer simulation results using experimental raw data are provided, to demonstrate the performance improvement against the conventional methods.

Moving variance-based signal quality monitoring method for spoofing detection

Signal quality monitoring (SQM) techniques, originally designed for multipath detection, were recently found to be useful to identify underway spoofing attacks. Conventional SQM-based methods directly employ the values of the SQM metrics to monitor spoofing attacks. They have good feasibility with simple structures but suffer from significant performance loss for frequency unlocked spoofing cases due to the drift of the relative carrier phase. We developed an enhanced SQM technique for detecting an onset of spoofing. It is known that the value of the SQM metric fluctuates significantly during the interaction stage between the counterfeit signal and authentic signal. As the variance of metric can better reflect this fluctuation, we choose the moving variance (MV) of the SQM metric as a new metric to detect the occurrence of spoofing. The basic principle of the proposed method is introduced. Its ability to detect spoofing has been validated using the Texas Spoofing Test Battery dataset and compared with the classic SQM methods and a moving average-based method. The results show that the proposed MV-based SQM method is advantageous in the detection of an onset of a frequency unlocked spoofing attack.

A New Signal Quality Monitoring Method for Anti-spoofing

Intermediate spoofing, identified as an efficient spoofing attack method, can launch a spoofing attack without interrupting the regular functioning of Global Navigation Satellite System (GNSS) receivers. GNSS is vulnerable and easily interfered by spoofing because of its opening signal structure and low signal power, and this threatens the security and integrity of GNSS, especially for the safety critical applications such as maritime and aviation. Signal Quality Monitoring (SQM) techniques, originally designed for multipath detection, are recently found to be useful to identify the deformation on the correlation function of a GNSS signal due to an intermediate spoofing attack. Conventional SQM-based methods directly employ the values of the SQM metric to detect spoofing attacks. In this paper, we develop an enhanced SQM technique for spoofing detection. It is known that the value of SQM metric fluctuates significantly during the interaction between the counterfeit signal and authentic signal. As the variance of metric can better reflect this fluctuation of metric, we choose the moving variance (MV) of the SQM metric as a new “metric” to detect the occurrence of spoofing. The basic principle of the proposed method is well introduced and tested on four different SQM metrics. Its ability to detect spoofing has been validated using the dataset collected using our SPIRENT simulators. The results show that the proposed moving variance-based SQM method is advantageous in the detection of spoofing attacks.

Dichotomous search of coarse time error in collective detection for GPS signal acquisition

Abstract Coarse time error (CTE) is an additional systematic absolute-timing-related bias that must be compensated in an assisted GPS (A-GPS)-based snapshot receiver where the complex baseband signal available for processing is finite and short. Resolving for CTE instead of waiting for the time of week string in the satellite’s navigation message allows A-GPS receivers to achieve faster time to first fix in cold start and warm start conditions. This paper highlights the problem of CTE that is conventionally resolved using coarse time positioning (CTP)—a least-squares-based algorithm. Following this, the same problem is shown to occur when collective detection (CD)—a direct position estimation algorithm—is applied in place of CTP. Previous literature on CD has not discussed nor presented any resolution to the CTE problem. Directly augmenting CTE to be resolved together with the user’s position and common clock bias in CD requires huge computational resources, which is impractical to be implemented using current generation consumer-grade computers. Therefore, the main contribution of this research is to propose and implement a dichotomous search jointly with CD to resolve for the CTE and position-common-clock-bias vector, respectively, at a relatively low computational burden. Empirical results using live satellite signals show that the proposed method is capable of effectively eliminating the positioning error biases caused by CTE. It is shown that the proposed compensation method can achieve equivalent performance to the conventional CTP method without losing the benefits of CD.