An estimation method based on the principle of the “miss distance tube” is proposed to obtain the practical miss distance of anti-aircraft missiles under low-precision measurement conditions of tests. The specific algorithms and examples are illustrated for the optical measurement data and Doppler frequency telemetry data. The results of examples show that the proposed method can produce a high-precision miss distance under low-precision measurement conditions， which is an effective means of using optical measurement data to estimate the miss distance. The proposed method has significant advantages and can better estimate the miss distance under the unknown relative velocity of the missile and the target. The method features simple and rapid algorithms， high precision， and good engineering applicability.

This paper aims to use the method of evidential reasoning （ER） algorithm based on fuzzy uncertainty to provide the basis for missile quality condition assessment， especially to deal with many unquantifiable factors， as well as factors which are inaccurate， unclear and incomplete. The ER algorithm operates in a system where both unknown and fuzzy data are modeled under the unified framework of distributed fuzzy belief structure to form a fuzzy belief decision matrix. Using the grade matching method， the numerical data and various forms of qualitative （fuzzy） evaluation information are finally transformed into fuzzy belief structure. This method can fuse the evaluation levels of important parameters without iteration on the premise of maintaining the independence with fast degradation speed， so as to improve the sensitivity and applicability of the evaluation process.