双基地雷达加密感知的扩展证明：统一分析与随机激活阵列
Extended Proofs for Encrypted Sensing in Bistatic Radar: Unified Analysis and Randomly Activated Arrays
- Tsinghua University（清华大学）
- University of Science and Technology Beijing（北京科技大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文为双基地雷达脉冲式空间随机化加密感知提供完整的SNRL数学推导，建立简化模型，推导渐近SNRL、有限CPI下的偏差方差及伯努利激活的闭式矩，补充主论文的证明。
AI中文摘要：
本补充材料提供了脉冲式空间随机化加密感知的信噪比损失（SNRL）分析的完整数学推导。我们首先推导了一个简化模型，其中发射端随机化由独立同分布的复空间系数表示。基于该模型，我们建立了几乎必然和均值的渐近SNRL，推导了有限相干处理间隔（CPI）下的前导偏差和方差，并为独立伯努利单元激活获得了闭式系数矩和渐近SNRL。这些结果补充了相关论文中的简明陈述和证明草图。
英文摘要：
This supplementary material provides the complete mathematical development for the signal-to-noise ratio loss (SNRL) analysis of pulse-wise spatially randomized encrypted sensing. We first derive a reduced model in which the transmit-side randomization is represented by an independent and identically distributed complex spatial coefficient. Based on this model, we establish the almost-sure and mean asymptotic SNRL, derive the leading bias and variance for a finite coherent processing interval (CPI), and obtain closed-form coefficient moments and asymptotic SNRL for independent Bernoulli element activation. These results complement the concise statements and proof sketches in the associated paper.
