Tatsuya Iwase

Estimation and exclusion of multipath range error for robust positioning

In integrated systems for accurate positioning, which consist of GNSS, INS, and other sensors, the GNSS positioning accuracy has a decisive influence on the performance of the entire system and thus is very important. However, GNSS usually exhibits poor positioning results in urban canyon environments due to pseudorange measurement errors caused by multipath creation, which leads to performance degradation of the entire positioning system. For this reason, in order to maintain the accuracy of an integrated positioning system, it is necessary to determine when the GNSS positioning is accurate and which satellites can have their pseudorange measured accurately without multipath errors. Thus, the objective of our work is to detect the multipath errors in the satellite signals and exclude these signals to improve the positioning accuracy of GNSS, especially in an urban canyon environment. One of the previous technologies for tackling this problem is RAIM, which checks the residual of the least square and identifies the suspicious satellites. However, it presumes a Gaussian measurement error that is more common in an open-sky environment than in the urban canyon environment. On the other hand, our proposed method can estimate the size of the pseudorange error directly from the information of altitude positioning error, which is available with an altitude map. This method can estimate even the size of non-Gaussian error due to multipath in the urban canyon environment. Then, the estimated pseudorange error is utilized to weight satellite signals and improve the positioning accuracy. The proposed method was tested with a low-cost GNSS receiver mounted on a test vehicle in a test drive in Nagoya, Japan, which is a typical urban canyon environment. The experimental result shows that the estimated pseudorange error is accurate enough to exclude erroneous satellites and improve the GNSS positioning accuracy.

Infra-free indoor positioning using only smartphone sensors

Though a variety of indoor positioning systems have been proposed for a GPS-denied environment, most of them depend on dedicated devices which must be installed in a building. The preparation of this infrastructure usually entails considerable cost, which prevents the spread of indoor positioning technology. On the other hand, smartphones are already widespread and their low cost sensors are promising as rich data sources that can be used for indoor navigation. Several studies have demonstrated the possibility of smartphone-based infrastructure-free positioning. However, this navigation is not yet practical because of the accumulative error of inertial sensors and the communication range measurement error. We propose a solution to reduce the accumulative error of pedestrian dead reckoning carried out with only the low cost sensors and WiFi in smartphones by realizing cooperative positioning among multiple pedestrians. Our proposed method introduces linkage structures to simplify trajectories of pedestrians; these structures work as a constraint to reduce the number of variables to be estimated. Since this constraint makes positioning problems solvable with a small number of observations, our proposed method screened WiFi data by the signal strength and selected only strong signals for use in positioning. Our testing results showed that the positioning accuracy improved as the number of participants in the cooperative positioning operation increased. The positioning uncertainty was a few meters, comparable to GPS, when the density of participants is high enough.

Self-Fulfilling Signal of an Endogenous State in Network Congestion Games

We consider the problem of coordination via signaling in network congestion games to improve social welfare deteriorated by incomplete information about traffic flow. Traditional studies on signaling, which focus on exogenous factors of congestion and ignore congestion externalities, fail to discuss the oscillations of traffic flow. To address this gap, we formulate a problem of designing a coordination signal on endogenous information about traffic flow and introduce a self-fulfilling characteristic of a signal that guarantees an outcome flow consistent with the signal itself without causing the unwanted oscillation. An instance of the self-fulfilling signal is shown in the case of a Gaussian signal distribution. In addition, we show simple numerical examples. The results reveal how a self-fulfilling signal suppresses the oscillation and simultaneously improves social welfare through improved network efficiency.

M-epoch ambiguity resolution technique for single frequency receivers with INS aid

Accurate positioning for land vehicles is required to meet the requirements of new safety systems. Though dual frequency RTK has sufficient accuracy for these needs, the cost makes it difficult for this to become common in consumer vehicles. The objective of this study is to realize commercially feasible RTK using practical single frequency receivers with the support of vehicle embedded gyros and odometers. The information of vehicle trajectory limits the ambiguity search space and improves the performance of single frequency RTK. A driving experiment showed that this approach has advantages both in a suburban area and urban canyon, compared to the traditional RTK.