The analyses were based on the satellite position dilution of precision (SPDOP) values as an indicator of precise orbit determination, and their reliability was demonstrated through evaluating the contribution of ground stations to track medium Earth orbit (MEO) and inclined geosynchronous orbit (IGSO) satellites of the BDS constellation. [PERSON] et al. [19] optimized GS deployment to track the MEO constellation of BDS-3. An algorithm was developed to optimize the GS number and deployment for BDS-3 orbit determination using the minimization of the dynamic parameters dilution of precision (DPDOP) as a criterion. The optimization was based on 10 ground stations located in China with additional optimal GS deployment. It was shown that when utilizing intersatellite links (ISLs) in one-way ranging only, the same accuracy was obtained as for the dynamic parameters but with fewer ground stations. Using the ISLs, the mean number of GSs was reduced from 55 to 47. [PERSON] et al. [20] analyzed the impact of using ISL observations with GSs on the orbit determination of BDS satellites, where only 10 regional GSs distributed in mainland China were used. It was concluded that the ISL ranging observations significantly improved the orbit determination accuracy of the BDS-3 satellite, as the radial component was improved from 48.0 cm to 4.1 cm. Heavy observing coverage (HC) is a metric commonly used for achieving observation coverage through multiple GSs. By definition, and according to [PERSON] et al. [21], a heavy observing coverage of \(k\)-order of GSs for monitoring or tracking satellite constellations represents the case where there is full-time observation of each satellite by at least \(k\) GSs at any time. In other words, if at any time, each satellite of a constellation is visible to at least \(k\) GSs, these GSs reach \(k\)-heavy observing coverage (\(k\)-HC). For \(k\)-heavy observing coverage, the observing rate of each satellite is 100%, while for \(k+1\) heavy, the coverage could be less than 100%, and the observing rate is defined as the time observed by k GSs divided by the full observation duration. In the study of [PERSON] et al. [21], an analytical method based on a quadruple coverage metric was used to optimize ground monitoring station deployment for tracking BDS MEO satellites. It was shown that quadruple coverage could be achieved using 18 GSs uniformly distributed across the globe. Genetic algorithm methods are widely used for the optimization problem in engineering; for example, [PERSON] et al. [22] used this method to solve the problem of GS placements for a mega LEO constellation to enable global continuous coverage communication. Evidently, the optimized number and deployment of GSs for tracking LEO satellites should be taken into consideration for a full LEO PNT system. The difficulties in the deployment of GSs basically arise from geographic factors such as the non-uniformity of the Earth. In addition to the complexity of solving the problem related to the mathematical formulation itself, 71% of the Earth cannot be used, since it is covered by oceans and seas. Nevertheless, the importance of GS deployment has become great in the navigation field as all performance services depend on the reliability of GSs.