This paper proposes an enhanced timing advance (TA) estimation approach for Low Earth Orbit (LEO) satellite communication networks. The main challenges in LEO satellite networks include large equivalent cell radius and significant frequency offsets due to satellite movement and beam footprint size. Traditional 5G TA estimation mechanisms are not directly applicable in these scenarios. The proposed approach includes a user-side time-frequency pre-compensation method that leverages frequency offset measurements from synchronization signal blocks during initial cell search. For the random access phase, the upper bound of inter-preamble interference is derived, and a cyclic prefix-free preamble format is designed to reduce interference and improve TA estimation accuracy. The proposed method reduces the missed detection rate of preambles within a beam, achieving lower than 1% missed detection rates for up to 64 users at -6 dB SNR. The TA estimation error is limited to the time length of 25 time-domain sampling points when the subcarrier spacing is 30 kHz and the operation frequency is 27 GHz. The approach also includes a flexible preamble format design that supports accurate TA estimation in large equivalent cell radius and frequency offset scenarios. The proposed method is validated through simulations and shows significant improvements in TA estimation accuracy compared to baselines. The key contributions include the development of a time-frequency pre-compensation method for UEs without GNSS capability, the derivation of the upper bound of inter-preamble interference, and the design of a flexible preamble format that reduces the negative impact of partial-period cross-correlation operations. The method is applicable to both regenerative and transparent satellites, and it can be extended to 4-step random access procedures. The approach is based on the analysis of inter-preamble interference and the design of a preamble format that minimizes interference and improves TA estimation accuracy. The proposed method is shown to be effective in reducing TA estimation errors and improving the performance of LEO satellite networks.This paper proposes an enhanced timing advance (TA) estimation approach for Low Earth Orbit (LEO) satellite communication networks. The main challenges in LEO satellite networks include large equivalent cell radius and significant frequency offsets due to satellite movement and beam footprint size. Traditional 5G TA estimation mechanisms are not directly applicable in these scenarios. The proposed approach includes a user-side time-frequency pre-compensation method that leverages frequency offset measurements from synchronization signal blocks during initial cell search. For the random access phase, the upper bound of inter-preamble interference is derived, and a cyclic prefix-free preamble format is designed to reduce interference and improve TA estimation accuracy. The proposed method reduces the missed detection rate of preambles within a beam, achieving lower than 1% missed detection rates for up to 64 users at -6 dB SNR. The TA estimation error is limited to the time length of 25 time-domain sampling points when the subcarrier spacing is 30 kHz and the operation frequency is 27 GHz. The approach also includes a flexible preamble format design that supports accurate TA estimation in large equivalent cell radius and frequency offset scenarios. The proposed method is validated through simulations and shows significant improvements in TA estimation accuracy compared to baselines. The key contributions include the development of a time-frequency pre-compensation method for UEs without GNSS capability, the derivation of the upper bound of inter-preamble interference, and the design of a flexible preamble format that reduces the negative impact of partial-period cross-correlation operations. The method is applicable to both regenerative and transparent satellites, and it can be extended to 4-step random access procedures. The approach is based on the analysis of inter-preamble interference and the design of a preamble format that minimizes interference and improves TA estimation accuracy. The proposed method is shown to be effective in reducing TA estimation errors and improving the performance of LEO satellite networks.