###### Abstract
In addition to the previously discussed research on doppler frequency shift positioning technology for LEO satellite signals of opportunity, the current research also explores positioning technologies utilizing angle-of-arrival estimation and time difference of arrival for LEO satellite signals of opportunity. In 2015, [PERSON], [PERSON], and [PERSON] proposed the angle of arrival-based target localization method with the LEO satellite observer. This positioning method uses spherical trigonometry and singular value decomposition (SVD) to directly achieve target localization [21]. In 2021, [PERSON], [PERSON], and [PERSON] proposed the single differenced doppler positioning method with low Earth orbit signals of opportunity and angle of arrival estimation. With the AOA estimates and differential doppler positioning, neither base stations nor mobile receivers require precise knowledge of the LEO satellite states [22]. In 2024, [PERSON] et al. proposed coarse positioning technology through angle-of-arrival estimation of signals of opportunity based on the LEO satellite. The AOA estimation is done in real time using phase interferometry through a dedicated hardware architecture, and the final positioning accuracy demonstrates the effectiveness of the positioning technology [23]. In 2022, [PERSON] and [PERSON] proposed an alternative PNT based on the time difference of arrival (TDOA) of LEO signals of opportunity. Based on the LEO signals, no a priori knowledge of the LEO orbit parameters nor the time of transmission of the signals is assumed [24]. In summary, research teams worldwide have extensively studied and analyzed the positioning technology for LEO communications satellites using signals of opportunity (SOPs). With the rapid expansion of LEO constellations, the number of satellites is increasing exponentially, posing the challenge of selecting the appropriate satellite for positioning when multiple satellites are observed simultaneously. To address this, scholars have engaged in various studies. As early as the 1980s, [PERSON] and [PERSON] suggested that the influence of satellite selection on positioning accuracy could be quantified by the Geometric Dilution of Precision (GDOP), where a smaller GDOP indicates higher positioning accuracy [25]. Over the years, satellite selection based on GDOP has evolved into three main approaches: minimizing the number of GDOP calculations, recursively searching and calculating the GDOP, and treating the GDOP calculation as a constrained combinatorial optimization problem. However, most GDOP research has focused on mid- to high-orbit constellations specifically designed for navigation and positioning. In 2023, [PERSON], [PERSON], and colleagues proposed a fast satellite selection algorithm for positioning in LEO constellations. This algorithm is applicable to both user terminals with limited satellite signal access and ground stations with extensive access that outperform quasi-optimal, rotation partitioning, and recursive algorithms [26]. Building on previous studies, this manuscript primarily investigates satellite selection strategies and methods for SOPs positioning using LEO communication satellites, emphasizing three critical factors affecting positioning accuracy: satellite observable time, satellite elevation, and Position Dilution of Precision (PDOP). This constitutes the main contribution and highlight of the paper. The proposed method is applicable not only to the Starlink constellation but also to other LEO constellations. The remainder of the paper is structured as follows: Section 2 delves into the principles of positioning using (SOPs) of low Earth orbit (LEO) communication satellites. Section 2.3 introduces the concept of position dilution of precision (PDOP). Section 3 investigates the impact of satellite elevation and orbital altitude on positioning accuracy, based on studies conducted by other scholars. Section 4 proposes a satellite selection strategy for LEO communication satellites' SOPs-based navigation and positioning, informed by the preceding analysis.