基于双波段红外辐射信息的机载无源定位算法

针对纯方位被动定位跟踪技术收敛时间偏长无法满足空战要求的问题, 通过增加观测方程的测量信息,提出了一种基于双波段红外无源辐射信息的被动定位算法,建立了双波段融合定位的数学模型,给出了相应的卡尔曼滤波方程,然后对模型进行了仿真验证.该方法在传统被动定位测量方程中增加了红外光谱辐射信息,提高了无源定位的收敛速度和精度.此外,由于改进数学模型把长波段红外辐射信息增加到测量方程中,提高了机载红外搜索跟踪系统在目标前半球进行跟踪的能力,非常有利于飞机实现对空中目标的全向探测.

Airborne Passive Measurements Algorithm Based on Double Wave Band Infrared Information

Bearings-only target tracking appears inadequate for convergence obtaining passive measurements of position and velocity of aerial target. A novel approach for passive measurements was proposed, which increased the infrared radiance information in the measurement equation in order to improve the filter capability. The proposed algorithm was explained; a briefing was given. Then the proposed algorithm was used to estimate the position and velocity of aerial target by its angular information and infrared radicalization information. A lengthy mathematical derivation was given which included eqs. (1) through (11). Eq. (4) is the key equation in proposed algorithm. A simulation example was given. Figs.2 and 4 show the variation of position error in km over a period of 100s under certain conditions; Figs.3 and 5 show the variation of velocity error in km/s over a period of 100s under certain conditions. These simulation results show that the algorithm proposed looks promising for making passive measurements of position and velocity of aerial target sufficiently accurate.