## 1 Introduction  
Compared to microwave communication, free-space optical communication offers various advantages, including high speed, high confidentiality, low power consumption, and small size; it is therefore widely used in interstellar, inter-satellite, and satellite-to-ground links [1, 2, 3, 4]. Using beacon light in laser communication can enhance the likelihood of acquisition and shorten the time required to establish laser communication links [5, 6]. However, the utilization of wide-beam divergent beacon light in laser communication exacerbates the loss of spatial energy and renders it susceptible to interference from background radiation and detector noise, thereby diminishing the precision of beacon-light position detection. The precision of beacon-light position detection plays a critical role in shaping the maintained establishment of system communication links [7]. Therefore, in long-range laser communication, employing beacon light presents challenges that are associated with establishing dynamic laser links in a stable manner, consequently restricting the utilization of beacons in laser communication. The quadrant detector (QD), characterized by its high sensitivity, fine resolution, and rapid responsivity, is extensively employed in laser communication for the precise measurement and tracking of position [8]. In order to achieve the stable establishment of links in laser communication systems, in recent years, researchers have endeavored to explore methodologies aimed at enhancing the precision of QD position detection. In [9], the nonlinear characteristics of spot detection positions are analyzed, and a linear correction method based on the Boltzmann function is proposed. In [10], error compensation factors and detector gap sizes are introduced into the spot position-detection model while digital filtering is applied to the detected light signals, thus enhancing the precision of spot position detection. In [11; 12], a neural network for backpropagation is constructed by analyzing measurement data, and a neural network-based method that enhances the measurement precision of QD is presented. In [13], a new and improved polynomial fitting algorithm for position detection that improves the linear range and precision of QD is proposed. In [14], two algorithms, the integral infinite log-ratio algorithm, and an integral infinity log-ratio algorithm based on the signal-to-noise ratio are proposed for QD position detection. The appropriate algorithm is selected based on the SNR of the received signal to achieve higher measurement accuracy. The aforementioned studies primarily focus on enhancing the precision of detection through the refinement of localization algorithms. However, the principal factor contributing to the degradation of the precision of QD spot position detection is the signal-to-noise ratio (SNR) of the detection signal [15]. In the event of a low SNR in the QD detection signal, achieving the high-precision detection of the spot centroid position becomes challenging when using the aforementioned methods. In some cases, the signal-to-noise ratio of the QD detection signal is low. In [16], the cyclic cross-correlation method is utilized to denoise the modulated sine-wave beacon light, resulting in a detection root-mean-square error one-quarter of that of the direct position-detection method. In [17], the Kalman filter is applied to process the modulated sine-wave beacon light, leading to a reduction in the detection root-mean-square error to 51.5%. However, its effect on improving detection accuracy was limited. Different from previous detection technologies, this article proposes a simple method that relies solely on On-Off Keying (OOK) modulation. This method not only achieves high-precision detection but also incorporates beacon communication multiplexing technology. In this study, we applied spread-spectrum technology to QD detection.