战场侦察雷达目标的自动识别

针对目前我国战场侦察雷达目标的识别主要靠人工完成这一现象，重点对战场上的几种典型地面活动目标－步兵、卡车和坦克回波多卜勒频谱进行分析，寻求几类目标的自动识别方法，以弥补对目标进行人工识别存在的诸多缺陷，适应现代战争的需求。首先进行步兵和机动车目标的区分，根据目标回波瞬时频率变化的不同，即步兵目标的回波瞬进频率变化具有一定的周期性，依此实现了步兵和机动车目标的区分。然后在机动车目标中将坦克和卡车目标加以区分，经研究发现坦克目标具有独特履带特性，根据这一特征便可将坦克目标和卡车目标区分开来。经实验室统计和现场检验，该方法对步兵、卡车、坦克三类目标进行分类识别的总识别率可达85％以上，证明了该方法的有效性。

Automatic identification of targets detected by battlefield scout radar

Aimed at the phenomena that identification of targets detected by the battlefield scout radar is mainly completed artificially in our country, Doppler spectrum of several typical targets moving on the battlefield, such as infantry, truck and tank are analyzed in order to seek a method for automatically identifying these targets. The automatic identification of targets can avoid many shortcomings of artificial identification and accommodate the need of modern wars. Infantry and motor vehicle will be identified firstly. According to differences of target's instantaneous frequency variation, that is, the instantaneous frequency variation of infantry has periodicity, Infantry and motor vehicle are identified. Next motor vehicle should be identified to truck or tank. Features of track owned by tank is found by studying spectrum of truck and tank, so they can be identified by these features. Through statistics in laboratory and verification in practice the identification rate of these targets is proved over 85 percent, and this proved the method is efficient.