In the existing velocity filtering based track-before-detect (VF-TBD), target existence is generally assumed to be constant, and multiple successive frames in a sliding window are jointly processed. However, when the target existence changes abruptly in a processing batch, the incorporation of noise-only frames may corrupt target energy integration. This results in degraded detection and estimation performances with serious decision delays. A pseudo-spectrum based VF-TBD is proposed to effectively detect and track targets with existence uncertainty. An adaptive integration strategy is developed to realise effective energy accumulation with only informative frames by matching target appearance and disappearance times in addition to the velocity. The change of target existence can be discovered in time, and the decision delay is reduced. An estimation strategy based on the maximum output SNR is presented to supply accurate estimations of not only target motion parameters (including the position and velocity) but also time parameters (including appearance and disappearance times). The target output envelope, SNR gain and receiver operating characteristic curve of targets with uncertain existence are analysed theoretically. Numerical simulations exhibit the validity of the proposed method.

中文翻译：

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基于自适应伪谱的不确定存在目标检测前追踪

在现有的基于速度过滤的检测前跟踪（VF-TBD）中，通常假设目标存在是恒定的，并且联合处理滑动窗口中的多个连续帧。然而，当目标存在在处理批次中突然变化时，仅噪声帧的合并可能会破坏目标能量积分。这导致检测和估计性能下降，并导致严重的决策延迟。提出了一种基于伪谱的VF-TBD来有效地检测和跟踪存在不确定性的目标。开发了一种自适应集成策略，通过匹配目标出现和消失时间以及速度，仅使用信息帧来实现有效的能量积累。能够及时发现目标存在的变化，减少决策延迟。提出了一种基于最大输出信噪比的估计策略，不仅可以准确估计目标运动参数（包括位置和速度），还可以准确估计时间参数（包括出现和消失时间）。对不确定存在目标的目标输出包络、信噪比增益和接收机工作特性曲线进行了理论分析。数值模拟证明了该方法的有效性。