To provide competitive global positioning and timing services under the condition that monitoring stations are confined to Chinese territory, inter-satellite link (ISL) technology is used by the third-generation BeiDou Navigation Satellite System (BDS-3). The ISL, together with the dual one-way links between satellites and anchor stations, may enable autonomous navigation for BDS-3. In this paper, we propose a general observation model for orbit determination (OD) and time synchronization (TS) directly using non-simultaneous observations, such as raw ISL pseudoranges. With the proposed model, satellite orbits, clocks, and hardware delay biases of ISL equipment can be determined simultaneously by jointly processing inter-satellite one-way pseudorange data and observation data from ground monitoring stations. Moreover, autonomous OD and TS are also achievable with one-way pseudorange data from anchor stations and satellites. Data from eight BDS-3 satellites, two anchor stations, and seven monitoring stations located in China were collected to validate the proposed method. It is shown that by jointly processing data from the ISL and seven monitoring stations, the RMS of overlap orbit differences in radial direction is 0.019 m, the overlap clock difference (95%) is 0.185 ns, and the stability of the estimated hardware delay biases for each satellite is greater than 0.5 ns. Compared with the results obtained with the seven stations, the improvements of orbits in radial direction and clocks are 95.7% and 90.5%, respectively. When the hardware delay biases are fixed to predetermined values, the accuracies of orbits and clocks are further improved. By jointly processing pseudoranges from the satellites and the two anchor stations, the RMS of overlap orbit differences is 0.017 m in the radial direction, and the overlap clock difference (95%) is 0.037 ns. It has also been demonstrated that under the condition of one-way ranging links, the accuracies of orbits and clocks obtained by the above two modes are still significantly better than those obtained by using the data from the monitoring stations alone.