Location estimation and tracking for mobile stations (MSs) have attracted a significant amount of attention in recent years. In indoor environment where the signals from global positioning system (GPS) are either weak or blocked, signal sources from long term evolution advanced (LTE-A) system can be adopted to provide location estimation for MS. Based on the range signals from both macro base station (mBS) and femto BS (fBS) in LTE-A heterogeneous networks (HetNet), we propose femto-assisted location estimation (FALE) schemes to estimate MS's position especially for indoor environments with insufficient signal inputs from mBSs. Since fBSs are usually deployed by users in their residential or business buildings, the locations of these fBSs generally cannot be known exactly. We depict the imprecise fBSs' positions as belief information to investigate a Bayesian estimation method based on the time difference of arrival (TDOA) measurement, and utilize particle filtering technique to develop the FALE algorithm. Moreover, a simplified FALE (FALE-S) scheme is proposed to reduce the computation cost resulting from the particle filter in original FALE method. Performance evaluation is conducted based on the LTE-A HetNet environments. Compared to conventional scheme, simulation results show that the proposed FALE algorithms can provide better location estimation of MS through the assistance of fBSs.