Initial orbit determination with angles-only data is a classical problem in space exploration that has been explored using only three angles-only data and multiple angles-only data [6; 7; 8]. Orbit determination algorithms that do not require the initial value of the target orbit can be roughly divided into two types. The first type is an initial orbit determination algorithm based on [PERSON]'s algorithm and the admissible region algorithm [9; 10; 11; 12]. Such techniques fit the angular data to obtain angular changes or even second-order changes [13; 14; 15]. The second type is an initial orbit determination algorithm based on the Gaussian method, \(\mathrm{L_{n}}\) algorithm, and the unit vector method (UVM) [6; 8; 16]. These techniques calculate the initial values by approximating the constant Lagrangian coefficients under the short-observed arc segment data. An iterative process is designed to solve for the initial orbit exactly. These methods can also be further divided according to different algorithms, including distance-as-a-variable and a UVM with position and velocity as variables. However, large systematic errors exist when more than three distances at different moments in time are used as orbital parameters. Several studies have focused on improving the UVM for cases of perturbation and long arc segments [17; 18]. According to the UVM, a covariance matrix close to the analytic relationship can be obtained using the linear equations of position and velocity when the observation arc is short. In this paper, the geometric dilution of precision (GDOP), obtained through the covariance matrix, is used to compare the initial orbit determination accuracy under different observation geometries [19]. The example of an optical sensor observing a single target over a long period of time is given, and the initial orbit is calculated using the UVM in different visible arc segments. The covariance matrix of the target state is then calculated using Monte Carlo simulation to verify whether the method of approximating the Lagrangian coefficient and distance to a constant value is reasonable. Various factors affect the GDOP of the target state in the orbital solution, including the observation error, continuous observation arc length, and observation geometry. The first two variables depend more on the performance of the optical sensor; the final variable represents the relative geometric positional relationship between the optical sensor and the target. Studying the effect of observation geometry on the initial orbit determination of short-arc angles-only data can help to understand the surveillance capability of space surveillance systems in different regions in space. When the initial orbit is calculated using three angles-only data by the Laplacian method or the Gaussian method [6; 20], it is generally considered that the orbit solution is very sensitive to measurement errors when the angle between the target and the optical sensor orbit plane is close to \(0^{\circ}\). It can be argued that the optical sensor has a poor surveillance capability for such targets. [PERSON] [20] obtained the preconditions for the convergence of the Gaussian iterations by calculating the signal-to-noise ratio of the line-of-sight determinant. Therefore, the angle between the target and optical sensor orbital planes is an important factor affecting the observation geometry. By taking the example of an optical sensor observing a single non-coplanar target over a long time, the solution for the initial orbit cyclically incurs large errors. The goal of this study is to analyse the characteristics of the influence of the observation geometry on initial orbit determination. During space target surveillance, the observation geometry can be fully determined using the orbital parameters of the target and the optical sensor. Twelve independent parameters are required to describe the orbital parameters of the target and the optical sensor.