## 1 Introduction
If there is no Reference Station (RS) receiver capable of assisting the user, here is an example of information that will be described in the HS-CGR cognitive layer:  
* Depending on the type of receiver start-up (cold/warm/hot): use relevant information in the receiver or perform the normal process. * According to \(C/N_{0}\) level: use high sensitivity techniques (long coherent integration with non-coherent accumulation). Figure 1: Smart functional architecture of a HS-SGR. * Depending on the number of received GNSS signals: track more powerful signal by standard tracking or combine various available signals using collective detection. When there are less than four satellites that can be detected individually, CD can still provide a coarse positioning solution with attenuated signals in a challenging environment. CD can be seen both as a high sensitivity and a direct positioning method because it provides a coarse estimation of the user position using direct navigation solution [3]. The CD approach is able to process weak GNSS signals, but is however, computationally intensive because of the important number of candidate points considered to search the position and the available assistance data. The computational load is even greater if the CD process is performed using the accumulation of all visible satellites which makes its practical implementation very difficult [6; 7; 8; 9; 10]. Thus, this paper proposes a method that consists in choosing the best surrounding receiver from several connected receivers to serve as a reference station to assist other receivers in difficulty, in a smart cooperative navigation set-up. In this proposal, various parameters will be taken into consideration when choosing the best reference receiver. Then, new metrics of the CD involving an optimal weighting of visible satellites will be exploited. An optimization method will be analyzed in order to ensure that the best satellites are used in the CD process according to certain defined parameters such as the elevation mask angle, the signal power (\(C/N_{0}\)), and the geometry of the satellite constellation (Geometric dilution of precision--GDOP). In order to ensure a better sensitivity performance in the CD process, with the best receiver chosen from among several connected receivers, the Spectral Peak Location (SPL) delta corrected FFT technique, developed in [11], is used for Doppler estimation. It can be seen that this proposal provides certain advantages in terms of complexity and sensitivity performance, compared to other Doppler estimation techniques in the position and velocity domain as [12]. The rest of the paper is structured as follows: the CD principle is presented in Section 2. Then, Section 3 develops the proposed smart collaborative positioning using the CD approach (smart high sensitivity receiver). In Section 3, we present the influence of certain parameters in the CD process, the principle of exploitation of best satellites while presenting the new metrics of CD and the algorithm of smart CD using the best satellites. Results with real GNSS signals will be presented in Section 4 to show the efficiency of the proposed method. Finally, we conclude the paper with a discussion about the overall performance achieved with this proposal, the contribution of this work and the outstanding issues to be covered in future work.