The BGPsec protocol, which is an extension of the border gateway protocol (BGP) for Internet routing known as BGPsec, uses digital signatures to guarantee the validity of routing information. However, the use of digital signatures in routing information on BGPsec causes a lack of memory in BGP routers, creating a gaping security hole in today's Internet. This problem hinders the practical realization and implementation of BGPsec. In this paper, we present APVAS (AS path validation based on aggregate signatures), a new protocol that reduces the memory consumption of routers running BGPsec when validating paths in routing information. APVAS relies on a novel aggregate signature scheme that compresses individually generated signatures into a single signature. Furthermore, we implement a prototype of APVAS on BIRD Internet Routing Daemon and demonstrate its efficiency on actual BGP connections. Our results show that the routing tables of the routers running BGPsec with APVAS have 20% lower memory consumption than those running the conventional BGPsec. We also confirm the effectiveness of APVAS in the real world by using 800,000 routes, which are equivalent to the full route information on a global scale.

Cloud-based Global Navigation Satellite Systems (CB-GNSS) positioning architecture that offloads part of GNSS positioning computation to cloud/edge infrastructure has been studied as an architecture that adds valued functions via the network. The merits of CB-GNSS positioning are that it can take advantage of the abundant computing resources on the cloud/edge to add unique functions to the positioning calculation and reduce the cost of GNSS receiver terminals. An issue in GNSS positioning is the degradation in positioning accuracy in unideal reception environments where open space is limited and some satellite signals are blocked. To resolve this issue, we propose a satellite selection algorithm that effectively removes the multipath components of blocked satellite signals, which are the main cause of drop in positioning accuracy. We build a Proof of Concept (PoC) test environment of CB-GNSS positioning architecture implementing the proposed satellite selection algorithm and conduct experiments to verify its positioning performance in unideal static and dynamic conditions. For static long-term positioning in a multipath signal reception environment, we found that CB-GNSS positioning with the proposed algorithm enables a low-end GNSS receiver terminal to match the positioning performance comparable to high-end GNSS receiver terminals in terms of the FIX rate. In an autonomous tractor driving experiment on a farm road crossing a windbreak, we succeeded in controlling the tractor's autonomous movement by maintaining highly precise positioning even in the windbreak. These results indicates that the proposed satellite selection algorithm achieves high positioning performance even in poor satellite signal reception environments.

The carrier-phase multipath effect can seriously affect the accuracy of GPS-based positioning in static short baseline applications. Although several kinds of methods based on time domain and spatial domain techniques have been proposed to mitigate this error, they are still limited by the accuracy of the multipath model and the effectiveness of the correction strategy. After analyzing the existing methods, a new method based on adaptive thresholding wavelet packet transform (AW) and time domain bootstrap spatial domain search strategy (TB) is presented (AWTB). Taking advantage of adaptive thresholding wavelet packet transform, we enhance the precision of the correction model and the efficiency of the extraction method. In addition, by adopting the proposed time domain bootstrap spatial domain strategy, the accuracy and efficiency of subsequent multipath correction are improved significantly. Specifically, after applying the adaptive thresholding wavelet packet method, the mean improvement rate in the RMS values of the single-difference L1 residuals is about 27.93% compared with the original results. Furthermore, after applying the proposed AWTB method, experiments show that the 3D positioning precision is improved by about 38.51% compared with the original results. Even compared with the method based on stationary wavelet transform (SWT), and the method based on wavelet packets denoising (WPD), the 3D precision is improved by about 26.94% over the SWT method and about 22.96% over the WPD method, respectively. It is worth noting that, although the mean time consumption of the proposed algorithm is larger than the original method, the increased time consumption is not a serious burden for overall performance.

We have already proposed synchronized spread spectrum code division multiple access (SS-CDMA) for the Quasi-Zenith Satellite System (QZSS) safety confirmation system to be used in times of great disaster. In this system, the satellite reception timings of all uplink signals are synchronized using a transmission timing control method in order to realize high-density user multiple access. An issue that should be addressed in order for this system to be viable is the error that can occur in the satellite reception timing. This error occurs due to the terminal time deviation and the error in calculating the propagation delay to the satellite. In this paper, we measure the terminal time deviation and the propagation delay calculation error at the same time by using the same receivers and evaluate the satellite reception timing error of the uplink signal. By this measurement, it is shown that satellite reception timing error within 50ns can be realized in 99.98% of mobile terminals. This shows that the synchronized SS-CDMA with the transmission timing control method has a potential to realize the QZSS short message system with high-density user multiple access.

Cell phones with GPS function as well as GPS loggers are widely used and we can easily obtain users' geographic information. Now classifying the measured GPS positions into indoor/outdoor positions is one of the major challenges. In this letter, we propose a robust indoor/outdoor detection method based on sparse GPS measured positions utilizing machine learning. Given a set of clusters of measured positions whose center position shows the user's estimated stayed position, we calculate the feature values composed of: positioning accuracy, spatial features, and temporal feature of measured positions included in every cluster. Then a random forest classifier learns these feature values of the known data set. Finally, we classify the unknown clusters of measured positions into indoor/outdoor clusters using the learned random forest classifier. The experiments demonstrate that our proposed method realizes the maximum F1 measure of 1.000, which classifies measured positions into indoor/outdoor ones with almost no errors.

This letter proposes a new positioning method for WLAN (Wireless Local Area Network) systems based on a principle of the RTK-GPS (Real Time Kinematic-Global Positioning System). The proposed method collects observations of the carrier phase at access points for a double phase difference of the RTK-GPS. We show a numerical example for evaluations of the proposed method considering the measurement error by computer simulations.

For capacity expansion of the Quasi-Zenith Satellite System (QZSS) safety confirmation system, frame slotted ALOHA with flag method has previously been proposed as an access control scheme. While it is always able to communicate in an optimum state, its maximum channel efficiency is only 36.8%. In this paper, we propose adding a reservation channel (R-Ch) to the frame slotted ALOHA with flag method to increase the upper limit of the channel efficiency. With an R-Ch, collision due to random channel selection is decreased by selecting channels in multiple steps, and the channel efficiency is improved up to 84.0%. The time required for accommodating 3 million mobile terminals, each sending one message, when using the flag method only and the flag method with an R-Ch are compared. It is shown that the accommodating time can be reduced to less than half by adding an R-Ch to the flag method.

Compressed Sensing (CS) is known to provide better channel estimation performance than the Least Square (LS) method for channel estimation. However, multipath delays may not be resolved if they span between the grids. This grid problem of CS is an obstacle to super resolution channel estimation. An Atomic Norm (AN) minimization is one of the methods for estimating continuous parameters. The AN minimization can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. There are studies showing that the AN minimization method has better resolution than conventional CS methods. In this paper, we propose a channel estimation method based on the AN minimization for Spread Spectrum (SS) systems. The accuracy of the proposed channel estimation is compared with the conventional LS method and Dantzig Selector (DS) of the CS. In addition to the application of channel estimation in wireless communication, we also show that the AN minimization can be applied to Global Positioning System (GPS) using Gold sequence.

Data breach and data destruction attack have become the critical security threats for the ICT (Information and Communication Technology) infrastructure. Both the Internet service providers and users are suffering from the cyber threats especially those to confidential data and private information. The requirements of human social activities make people move carrying confidential data and data breach always happens during the transportation. The Internet connectivity and cryptographic technology have made the usage of confidential data much secure. However, even with the high deployment rate of the Internet infrastructure, the concerns for lack of the Internet connectivity make people carry data with their mobile devices. In this paper, we describe the main patterns of data breach occur on mobile devices and propose a secure in-depth file system concealed by GPS-based mounting authentication to mitigate data breach on mobile devices. In the proposed in-depth file system, data can be stored based on the level of credential with corresponding authentication policy and the mounting operation will be only successful on designated locations. We implemented a prototype system using Veracrypt and Perl language and confirmed that the in-depth file system worked exactly as we expected by evaluations on two locations. The contribution of this paper includes the clarification that GPS-based mounting authentication for a file system can reduce the risk of data breach for mobile devices and a realization of prototype system.

Motorcycles are driven in a road widely but must be driven carefully because they are easily damaged by obstacles, bumps or potholes in the road. Thus, motorcycle trajectories are valuable for detecting road abnormalities. The trajectories are usually obtained from GPS (Global Positioning System). However, errors often occur in GPS positioning. In this research, we will present a detection idea of the GPS error based on behavior estimation of riders. Moreover, we will propose a novel behavior estimation method.

In this paper, a compact controlled reception pattern antenna (CRPA) array based on a mu-zero resonance (MZR) antenna is proposed for a global positioning system (GPS). The MZR antenna can be minimized by designing structure based in mu-negative (MNG) transmission line. The MNG transmission line can be implemented by a gap structure for the series capacitance and a shorting via for a short-ended boundary condition. The CRPA array, which operates in L1 (1.57542GHz) and L2 (1.2276GHz) bands, is designed as a cylinder with a diameter and a height of 127mm (5 inches) and 20mm, respectively, and is composed of seven radiating elements. To design the compact CRPA array with high performance attributes such as an impedance matching (VSWR) value of less than 2, an isolation between array elements (<-12dB), an axial ratio (<5dB), and a circular polarization (CP) gain (>-1dBic: L1 band and >-3dBic: L2 band), we employ two orthogonal MZR antennas, a superstrate, and chip couplers. The performances of the CRPA antenna are verified and compared by an analytic analysis, a full-wave simulation, and measurements.

With the extensive use of location based devices, trajectories of various kinds of moving objects can be collected and stored. As time going on, the volume of trajectory data increases exponentially, which presents a series of problems in storage, transmission and analysis. Moreover, GPS trajectories are never perfectly accurate and sometimes with high noise. Therefore, how to overcome these problems becomes an urgent task in trajectory data mining and related applications. In this paper, an adaptive noise filtering trajectory compression and recovery algorithm based on Compressed Sensing (CS) is proposed. Firstly, a noise reduction model is introduced to filter the high noise in GPS trajectories. Secondly, the compressed data can be obtained by the improved GPS Trajectory Data Compression Algorithm. Thirdly, an adaptive GPS trajectory data recovery algorithm is adopted to restore the compressed trajectories to their original status approximately. Finally, comprehensive experiments on real and synthetic datasets demonstrate that the proposed algorithm is not only good at noise filtering, but also with high compression ratio and recovery performance compared to current algorithms.

Cell phones with GPS function as well as GPS loggers are widely used and users' geographic information can be easily obtained. However, still battery consumption in these mobile devices is main concern and then obtaining GPS positioning data so frequently is not allowed. In this paper, a stayed location estimation method for sparse GPS positioning information is proposed. After generating initial clusters from a sequence of measured positions, the effective radius is set for every cluster based on positioning accuracy and the clusters are merged effectively using it. After that, short-time clusters are removed temporarily but measured positions included in them are not removed. Then the clusters are merged again, taking all the measured positions into consideration. This process is performed twice, in other words, two-stage short-time cluster removal is performed, and finally accurate stayed location estimation is realized even when the GPS positioning interval is five minutes or more. Experiments demonstrate that the total distance error between the estimated stayed location and the true stayed location is reduced by more than 33% and also the proposed method much improves F1 measure compared to conventional state-of-the-art methods.

Traffic signal phase and timing (TSPaT) information is valuable for various applications, such as velocity advisory systems, navigation systems, collision warning systems, and so forth. In this paper, we focus on learning baseline timing cycle lengths for fixed-time traffic signals. The cycle length is the most important parameter among all timing parameters, such as green lengths. We formulate the cycle length learning problem as a period estimation problem using a sparse set of noisy observations, and propose the most frequent approximate greatest common divisor (MFAGCD) algorithms to solve the problem. The accuracy performance of our proposed algorithms is experimentally evaluated on both simulation data and the real taxi GPS trajectory data collected in Shanghai, China. Experimental results show that the MFAGCD algorithms have better sparsity and outliers tolerant capabilities than existing cycle length estimation algorithms.

We have developed Pedestrian-Vehicular Collision Avoidance Support System (P-VCASS) in order to protect pedestrians from traffic accidents and its effectiveness has been verified. P-VCASS is a system that takes into account pedestrian's moving situations. It gives warning to drivers of neighboring vehicles in advance if there is a possibility of collision between vehicles and pedestrians. There are pedestrians to move around. They are dangerous for vehicle drivers because they have high probability of running out into the road suddenly. Hence, we need to take into account the presence of them. In this paper, we propose a new estimation method of pedestrian's running out into road by using pressure sensor and moving record. We show the validity of the proposed system by experiments using a vehicle and a pedestrian terminal in the intersection. As a result, we show that a driver of vehicle is able to detect dangerous pedestrians quickly and accurately.

The limitation of the GPS in urban canyon has led to the rapid development of Wi-Fi positioning system (WPS). The fingerprint-based WPS could be divided into calibration and positioning stages. In calibration stage, several grid points (GPs) are selected, and their position tags and featured access points (APs) are collected to build fingerprint database. In positioning stage, real time measurement of APs are compared with the feature of each GP in the database. The k weighted nearest neighbors (KWNN) algorithm is used as pattern matching algorithm to estimate the final positioning result. However, the performance of outdoor fingerprint-based WPS is not good enough for pedestrian navigation. The main challenge is to build a robust fingerprint database. The received number of APs in outdoor environments has large variation. In addition, positioning result estimated by GPS receiver is used as position tag of each GP to automatically build the fingerprint database. This paper studies the lifecycle of fingerprint database in outdoor environment. We also shows that using long time collected data to build database could improve the positioning accuracy. Moreover, a new 3D-GNSS (3D building models aided GNSS) positioning method is used to provide accurate position tags. In this paper, the fingerprint-based WPS has been developed in an outdoor environment near the center of Tokyo city. The proposed WPS can achieve around 17 meters positioning accuracy in urban canyon.

In this paper, a vehicular antenna design scheme that considers vehicular body effects is proposed. A wire antenna for the global positioning system (GPS) and long-term evolution (LTE) systems is implemented on a plastic plate and then mounted on a windshield of the vehicle. Common outputs are used to allow feed sharing. It is necessary to increase the GPS right-hand circularly polarization (RHCP) gain near the zenith and to reduce the axis ratio (AR). For LTE, we need to increase the horizontal polarization (HP) gain. In addition, for LTE, multiband characteristics are required. In order to achieve the specified performance, the antenna shape is optimized via a Pareto genetic algorithm (PGA). When an antenna is mounted on the body, antenna performance changes significantly. To evaluate the performance of an antenna with complex shape mounted on a windshield, a commercial electromagnetic simulator (Ansoft HFSS) is used. To apply electromagnetic results output by HFSS to the PGA algorithm operating in the MATLAB environment, a MATLAB-to-HFSS linking program via Visual BASIC (VB) script was used. It is difficult to carry out the electromagnetic analysis on the entire body because of the limitations of the calculating load and memory size. To overcome these limitations, we consider only that part of the vehicle's body that influences antenna performance. We show that a series of optimization steps can minimize the degradation caused by the vehicle`s body. The simulation results clearly show that it is well optimized at 1.575GHz for GPS, and 0.74 ∼ 0.79GHz and 2.11 ∼ 2.16GHz for LTE, respectively.

Incoming GPS signals through windows can be often observed indoors. However, conventional indoor positioning systems do not use Global Positioning System (GPS) generally because the signals may come in NLOS (Non Line of Sight). In this paper, we propose a positioning method by fingerprinting based on the incoming GPS signals.

This paper proposes a network clock system that detects degradation in the frequency accuracy of network clocks distributed across a network and finds the sources of the degradation. This system uses two factors to identify degradation in frequency accuracy and an algorithm that finds degradation sources by integrating and analyzing the evaluation results gathered from the entire network. Many frequency stability measurement systems have been proposed, and most are based on time synchronization protocols. These systems also realize avoidance of frequency degradation and identification of the sources of the degradation. Unfortunately, the use of time synchronization protocols is impractical if the service provider, such as NTT, has already installed a frequency synchronization system; the provider must replace massive amounts of equipment with new devices that support the time synchronization protocols. Considering the expenditure of installment, this is an excessive burden on service providers. Therefore, a new system that can detect of frequency degradation in network clocks and identify the degradation causes without requiring new equipment is strongly demanded. The proposals made here are implemented by the installation of new circuit cards in current equipment and installing a server that runs the algorithm. This proposed system is currently being installed in NTT's network.

TTFF (Time-To-First-Fix) is an important indicator of GPS receiver performance, and must be reduced as much as possible. Bit synchronization is the pre-condition of positioning, which affects TTFF. The frequency error leads to power loss, which makes it difficult to find the bit edge. The conventional bit synchronization methods only work well when there is no or very small frequency error. The bit synchronization process is generally carried out after the pull-in stage, where the carrier loop is already stable. In this paper, a new bit synchronization method based on frequency compensation is proposed. Through compensating the frequency error, the new method reduces the signal power loss caused by the accumulation of coherent integration. The performances of the new method in different frequency error scenarios are compared. The parameters in the proposed method are analyzed and optimized to reduce the computational complexity. Simulation results show that the new method has good performance when the frequency error is less than 25Hz. Test results show that the new method can tolerate dynamic frequency errors, and it is possible to move the bit synchronization to the pull-in process to reduce the TTFF.