Optoelectronic tracking systems enable the precise positioning, continuous tracking, and accurate measurement of targets in fields such as aeronautics, defense, and scientific exploration. Owing to their ability to perform high-precision tracking, these systems can adapt to complex electromagnetic environments and demonstrate remarkable efficacy in scenarios involving advanced aircraft. Owing to the development of new detectors and signal-processing technologies, optoelectronic tracking systems have incorporated higher performance detectors, utilized artificial intelligence (AI) algorithms, and transitioned from single-sensor to multimodal detections. Meanwhile, the demand for managing tasks involving multiple, high-speed, and weak targets in complex environments has increased. Therefore, the existing studies must be summarized to guide the future development of this field.

The technological solutions for optoelectronic tracking systems have evolved continually, with system structures changing from single-function to integrated designs (Fig. 1). Conventional optoelectronic tracking systems can be categorized into imaging and non-imaging types. Imaging systems, such as optical theodolites, infrared search and track systems (IRST), and electro-optical targeting systems (EOST), provide abundant image information, whereas non-imaging systems, such as Lidar for distance measurement and positioning and quadrant detectors for location determination, focus on high sensitivity and rapid tracking. In recent years, multimodal optoelectronic tracking systems have emerged. These systems, particularly those integrating optical and radar functionalities, offer advanced capabilities (Fig. 12). By combining infrared imagers, visible-light cameras, and radars, these systems afford higher measurement accuracies and enhanced capabilities, thus overcoming the limitations posed by single sensors under certain environmental conditions.

Photodetectors, as core components of optoelectronic tracking systems, directly affect the overall performance of the system. Owing to technological advancements, photodetectors are being developed to achieve higher sensitivities, larger pixel scales, and better signal-to-noise ratios (Table 1). Single-photon detectors, particularly single-photon avalanche diodes (SPAD) and superconducting nanowire single-photon detectors (SNSPDs), are preferred in optoelectronic tracking systems owing to their high sensitivity and long detection range. Additionally, infrared focal plane array (IR-FPA) detectors are crucial in optoelectronic tracking systems, particularly in scenarios requiring high resolutions and multisensor fusion.

Advancements in signal-processing technology are key to enhancing the performance of optoelectronic tracking systems. Conventional signal-processing methods, such as Kalman filtering and particle filtering, remain widely used. However, owing to the development of deep-learning technology, signal-processing methods based on the convolutional neural network (CNN) have emerged, e.g., the YOLO series, Siamese network, and Transformer plus CNN (Fig. 23). These methods can learn features from large datasets, thereby improving the accuracy of target recognition and enabling systems to perform autonomous search, identification, and tracking in complex environments.

Optoelectronic tracking systems are fundamental in the precise detection, positioning, and tracking of targets. Their performance is affected by the pixel scale, characteristics, and sensitivity of the detectors; the signal characteristics of detectors further determine the choice of appropriate signal-processing methods. Future advancements shall focus on multimodal detection, the innovation of detectors, and the development of intelligent signal-processing technologies. Through these advancements, optoelectronic tracking systems will be able to precisely detect, position, and track high-speed, long-range, and weak targets in complex environments.