To navigate in global navigation satellite systems (GNSS) signal-challenged environment, for example, foliage canopy, urban canyon, indoor, etc., high-sensitivity GNSS receivers are usually preferred for the improved acquisition and tracking capabilities. The core of high-sensitivity GNSS receiver design is to extend integration time coherently, which is optimal for improving post-signal-to-noise ratio, mitigating multipath and cross-correlation false locks, and avoiding squaring loss. In GNSS data channels, extending integration time coherently requires the navigation message data bit wipe-off. For stand-alone high-sensitivity GNSS receivers, bit wipe-off is usually achieved by using estimation algorithms (i.e., bit decoding) rather than accessing external networks (i.e., bit aiding). In this paper, the maximum-likelihood (ML) bit decoding is used to estimate the data bit values for bit wipe-off. Furthermore, the benefits of using advanced tracking algorithms-vector tracking and inertial navigation system (INS)-assisted tracking (i.e., ultratight coupling of GNSS/INS)-to improve ML bit decoding and navigation performance are analyzed. Two vehicular navigation tests are performed in dense foliage and an urban canyon environment. In the context of global positioning system L1 C/A signals, the field test results show that vector tracking and ultratight coupling can improve the successful decoding rate by up to 40% depending on signal strength. This paper also demonstrates how the signal power-based correlator selection method can address high bit error-rate problems when ML bit decoding is used for bit wipe-off in the signal-challenged environment. After implementing this algorithm, the position and velocity accuracy of the stand-alone high-sensitivity GNSS receiver has been improved about 50% after extending coherent integration time from 20 to 100 ms in the vehicular navigation tests.
