The increasing availability of low-Earth orbit (LEO) satellites, alongside the expected deployment of reflective intelligent surfaces (RISs), presents transformative opportunities for localization systems. LEO satellites can complement or serve as alternatives to global navigation satellite systems (GNSSs) [1], while RISs enhance both terrestrial networks (TN) and non-terrestrial networks (NTN) by providing additional, cost-effective location references. Unlike deploying base stations or satellites, RIS installations require minimal infrastructure while significantly improving localization accuracy and coverage.

Current research primarily focuses on RIS-aided localization in TN systems, while its application in NTN-based localization is still in its early stages [2]. In terrestrial systems, studies show that RIS can improve accuracy and coverage, even with one base station and single-antenna equipment [3]. However, the high attenuation of the base station-RIS-user path limits performance over long distances. This challenge can be addressed by deploying multiple RIS, as indicated by several sources on TN [4-6]. For NTN, early works have explored single RIS deployment and provided preliminary accuracy results [7]. However, research on multiple RIS is very little and primarily focuses only on performance bounds [2].

This study conducts a comparative analysis of key performance indicators (KPIs) for RIS-aided TN and NTN localization systems, focusing on the deployment of multiple RIS. The scenarios to be considered are shown in Fig. 1 and Fig. 2, respectively. Our contributions are threefold: (i) introducing a signal model and processing techniques for NTN RIS-aided localization with multiple RIS, (ii) analyzing and comparing different RIS phase profiles for separating RIS contributions and improving localization accuracy, and (iii) evaluating performance metrics such as accuracy, sensitivity, coverage, and dynamic range. Particular attention is given to the trade-offs between these metrics and the number of deployed RIS, as well as the comparative benefits of RIS-enhanced TN and NTN systems.