The last decade has witnessed a growing demand for precise positioning in many applications including car navigation. Navigating automated land vehicles requires at least sub-meter level positioning accuracy with the lowest possible cost. The Global Navigation Satellite System (GNSS) Single-Frequency Precise Point Positioning (SF-PPP) is capable of achieving sub-meter level accuracy in benign GNSS conditions using low-cost GNSS receivers. However, SF-PPP alone cannot be employed for land vehicles due to frequent signal degradation and blockage. In this paper, real-time SF-PPP is integrated with a low-cost consumer-grade Inertial Navigation System (INS) to provide a continuous and precise navigation solution. The PPP accuracy and the applied estimation algorithm contributed to reducing the effects of INS errors. The system was evaluated through two road tests which included open-sky, suburban, momentary outages, and complete GNSS outage conditions. The results showed that the developed PPP/INS system maintained horizontal sub-meter Root Mean Square (RMS) accuracy in open-sky and suburban environments. Moreover, the PPP/INS system could provide a continuous real-time positioning solution within the lane the vehicle is moving in. This lane-level accuracy was preserved even when passing under bridges and overpasses on the road. The developed PPP/INS system is expected to benefit low-cost precise land vehicle navigation applications including level 2 of vehicle automation which comprises services such as lane departure warning and lane-keeping assistance.

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Underwater target detection is mainly based on acoustic emissions generated by the target of interest (TOI) as it propels itself through the ocean, and operates non-propulsion-related onboard systems. The spectral signature of these acoustic emissions is used for identification and localization of TOI. This paper focuses on underwater target detection using passive sonobuoys. Discrete Fourier transform (DFT) is used in most sonobuoy processing systems to provide spectral analysis of the received signals. Due to the relatively high noise level and the several sources of interference that may exist underwater, the DFT may not determine the spectral signature of TOI with adequate accuracy. The low signal-to-noise ratio (SNR) and the presence of strong interference sources with frequencies close to the TOI frequency jeopardize the detection accuracy, the bearing estimation performance, and target tracking capabilities. The aim of this paper is to: (1) examine the performance of both wavelet packet analysis and high resolution spectral estimation techniques, and (2) provide a comparative study between both methods. Based on underwater acoustic simulation developed in this research, results showed that the proposed methods can achieve robust target detection with low levels of SNR and interferences of nearby signatures that cannot be detected by DFT.