Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

In this paper, a system that can collect GPS L1 C/A, GLONASS G1, and BDS B1I signals with single front-end receiver was implemented using a universal software radio peripheral (USRP) and its performance was verified. To acquire the global navigation satellite system signals, hardware was configured using USRP, antenna, external low-noise amplifier, and external oscillator. In addition, a value of optimum local oscillator frequency was selected to sample signals from three systems with L1-band with a low sampling rate as much as possible. The comparison result of C/N0 between the signal collection system using the proposed method and commercial receiver using double front-end showed that the proposed system had 0.7 ~ 0.8dB higher than that of commercial receiver for GPS L1 C/A signals and 1 ~ 2 dB lower than that of commercial receiver for GLONASS G1 and BDS B1I. Through the above results, it was verified that signals collected using the three systems with a single USRP had no significant error with that of commercial receiver. In the future, it is expected that the proposed system will be combined with software-defined radio (SDR) and advanced to a receiver that has a re-configuration channel.

The Wide Area Differential Global Positioning System (WADGPS) that uses a number of Global Navigation Satellite System (GNSS) reference stations are implemented with various types and provide services as it can service a wide range of areas relatively. This paper discusses a constellation design of reference stations and performance analysis of the WADGPS. It presented performance results of static and dynamic users when wide area correction algorithm was applied using eight reference stations.

In this paper, performance on receivers of multilateration (MLAT) system that uses ADS-B signal, which is recently becoming popular, was analyzed to overcome shortcomings of existing aircraft flight control systems or reinforce the capabilities. A link budget was analyzed using a channel model in the airport environment with regard to Local Area Multilateration (LAM) for ground-controlled landing around the airport. In order to detect signals that arrived at the receiver successfully, sensitivity of receiver was analyzed using a signal-to-noise ratio (SNR) worksheet, and a method that improves accuracy of the distance measurement was proposed by adopting a peak estimation using sampling signals. Through simulations, optimum specifications of receivers were analyzed to have high precision positioning of LAM, and accuracy of LAM distance measurements was presented.

In this paper, design and implementation issues for a network-oriented RF emitter localization system with array antenna are discussed. For hardware, the problem of array mismatch and RF/IF channel mismatch are introduced and the calibration schemes for solving those problems are also provided. For software, it is explained how to overcome the drawback of conventional MUltiple Signal Identification and Classification (MUSIC) algorithm in a point of identifying the number of received signals and problems such as Data Association Problem and Ghost Node Problem in regard to multiple emitter localization are presented with some approaches for getting around those problems. Finally, for implementation, a criterion for arranging each of sensors and a requirement for alignment of array antenna' orientation are also given.