We propose a novel method for blind bistatic radar parameter estimation (RPE), which enables integrated sensing and communications (ISAC) by allowing passive (receive) base stations (BSs) to extract radar parameters (ranges and velocities of targets), without requiring knowledge of the information sent by an active (transmit) BS to its users. The contributed method is formulated with basis on the covariance of received signals, and under a generalized doubly-dispersive channel model compatible with most of the waveforms typically considered for ISAC, such as orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS) and affine frequency division multiplexing (AFDM). The original non-convex problem, which includes an $\ell_0$-norm regularization term in order to mitigate clutter, is solved not by relaxation to an $\ell_1$-norm, but by introducing an arbitrarily-tight approximation then relaxed via fractional programming (FP). Simulation results show that the performance of the proposed method approaches that of an ideal system with perfect knowledge of the transmit signal covariance with an increasing number of transmit frames.

翻译：本文提出了一种用于盲双基地雷达参数估计的新方法，该方法通过使被动（接收）基站能够提取雷达参数（目标的距离和速度），而无需知晓主动（发射）基站向其用户发送的信息，从而实现了集成感知与通信。所提出的方法基于接收信号的协方差进行构建，并采用与大多数通常考虑用于ISAC的波形（如正交频分复用、正交时频空间和仿射频分复用）兼容的广义双弥散信道模型。原始非凸问题包含一个用于抑制杂波的ℓ₀范数正则化项，其求解并非通过松弛为ℓ₁范数，而是通过引入一个任意紧致的近似，随后利用分式规划进行松弛。仿真结果表明，随着发射帧数的增加，所提方法的性能逐渐逼近具有完美发射信号协方差知识的理想系统。