摘要：Navigation and positioning in harsh environments is still a great challenge for many applications. Collective Detection (CD) is a powerful approach for acquiring highly attenuated satellite signals in challenging environments, because of its capacity to process all visible satellites collectively taking advantage of the spatial correlation between GNSS signals as a vector acquisition scheme. CD combines the correlator outputs of satellite channels and projects them onto the position/clock bias domain in order to enhance the overall GNSS signal detection probability. In CD, the code phase search for all satellites in view is mapped into a receiver position/clock bias grid and the satellite signals are not acquired individually but collectively. In this concept, a priori knowledge of satellite ephemeris and reference location are provided to the user. Furthermore, CD addresses some of the inherent drawbacks of the conventional acquisition at the expenses of an increased computational cost. CD techniques are computationally intensive because of the significant number of candidate points in the position-time domain. The aim of this paper is to describe the operation of the CD approach incorporating new methods and architectures to address both the complexity and sensitivity problems. The first method consists of hybridizing the collective detection approach with some correlation techniques and coupling it with a better technique for Doppler frequency estimate. For that, a new scheme with less calculation load is proposed in order to accelerate the detection and location process. Then, high sensitivity acquisition techniques using long coherent integration and non-coherent integration are used in order to improve the performance of the CD algorithm.
