High-sensitivity continuous detection and tracking has gained widespread attention in the field of infrared surveillance of space dim targets. Moreover, studies on the infrared radiation and motion characteristics of targets are the premise of the system parameter design. High-speed air vehicles have strong maneuverability when the flight altitude and speed greatly fluctuate. Moreover, their angle of attack constantly changes and adjusts, showing a jumping trajectory during the flight. The radiant intensity reaching the entrance pupil of the detection system is low due to atmospheric absorption and changes drastically. Simultaneously, the background radiant intensity varies widely due to the complex and changeable earth background during flight, which reduces the detection efficiency of the traditional infrared detection system. However, current traditional detection systems using fixed parameters are unable to achieve high-sensitivity detection under all conditions when detecting targets with drastic changes in radiation and motion characteristics, leading to reduced system detection capability. Therefore, adaptively optimizing system parameters in real-time to ensure stable target detection and tracking is necessary. Additionally, it is necessary to propose a new detection method with real-time adaptive optimization of system parameters to ensure stable detection and tracking capabilities, thereby significantly improving the robustness of the system.

We propose a detection and tracking method via exposure time and integrating capacitor adaptive optimization using real-time image information. First, we develop a mathematical model of the system detection sensitivity decoupled from the target radiant intensity. The initial integration capacitance and exposure time are optimized to match the detector parameters with the optical system parameters using both the characteristics of the typical high-speed air vehicle motion and earth background radiation, respectively, and realizing a high-sensitivity search. Upon detecting the target and sustaining the tracking process, the target motion information and radiation information are collected. Subsequently, the target motion trajectory is fitted and the target center position in the next frame and motion speed are estimated. Additionally, we estimate the target center position and earth background radiation information in the next frame. From the formula (8), the optimal exposure time and the integration capacitance of the target tracking process are adaptively adjusted using the time-varying continuity of the target radiant intensity and the time-slow variability of the earth’s background radiation, keeping the target signal-to-noise ratio continuously optimal and achieving continuous tracking of the target.

A system detection spectrum of 2.7-3.0 μm is selected to suppress the earth’s background and ensure sufficient atmospheric transmittance. From the difference in background radiance, the earth’s background can be divided into the strong reflection background, such as high-altitude cirrus, and the conventional background, such as ocean, land, and low-altitude clouds whose typical radiance values are 2.4×10^-6 W/( sr·cm²) and 3.5×10^-7 W/( sr·cm²), respectively. We study the geosynchronous orbit satellite platform with the optical system parameters presented in Table 1. The typical speed of a high-speed air vehicle is 10 Ma. From the proposed mathematical model, the typical system exposure time is 158 ms, and the optimal full capacity is 3×10⁵ and 1×10⁶ under strong reflection and conventional backgrounds, respectively. Figure 5 shows the detection sensitivities under different working conditions. Figures 5(a) and 5(b) show system detection sensitivities for real-time parameter optimization and fixed system parameter detection methods, respectively. Using the fixed-parameter detection and adaptive parameter optimization methods, we can obtain detection sensitivities of up to 3 W/sr and 0.64 W/sr, respectively, thereby improving the detection capability by more than 4.5 times. For example, considering Falcon Hypersonic Technology Vehicle 2 (HTV2), whose entrance pupil radiant intensity goes as low as 200 W/sr, as shown in Fig. 6, the detectable radiant intensity threshold can reach up to 277 W/sr with the fixed parameter detection method, which fails to continuously detect and track HTV2. However, the radiant intensity threshold can be reduced to 195 W/sr using the real-time parameter optimization detection method, which meets the continuous detection and tracking requirements.

In this study, we propose a detection and tracking method using self-adaptive optimization of exposure time and integral capacitance. First, we optimize the initial system integration capacitance and exposure time using the target motion and background radiation characteristics. Notably, the actual target motion and surrounding background radiation characteristics are collected in real-time, and we adaptively adjust the optimal exposure time and integration capacitance, thus improving the detection and tracking performance. The numerical simulation results show that the system detection sensitivity is improved by up to 4.5 times using the real-time parameter optimization detection method, achieving the high-sensitivity target detection and tracking with the radiant intensity of 200 W/sr.