arXiv:2611.07803v1 Announce Type: new Abstract: This paper addresses a key challenge in bistatic integrated sensing and communications (ISAC): \textit{How to achieve reliable ranging using communication data signals that cannot be reliably recovered?} In modern communication systems, data payloads typically occupy far more time-frequency resources than pilots, offering substantially more observations to improve sensing accuracy. Exploiting them requires recovering the transmitted symbols to form sensing references. However, propagation and reflection losses can severely weaken target echoes. The sensing receiver may therefore be unable to recover data transmitted at a high rate selected for communication users. We first show that, at low signal-to-noise ratios (SNRs), using hard symbol decisions as sensing references can introduce a persistent bias in the estimated channel impulse response (CIR). This bias produces an error floor and spurious peaks in the power delay profile (PDP) that persist even after coherent accumulation over a large number of observations. To address this limitation, we develop a pilot-initialized expectation-maximization (EM) estimator that iteratively refines the CIR using posterior symbol moments. Under local regularity conditions and successful initialization, we establish that the EM method converges to the local maximum-likelihood (ML) solution for a sufficiently large number of OFDM data symbols. The converged estimator is asymptotically unbiased, where the CIR estimation mean-square error (MSE) at each delay bin decays as $O(1/M)$ by accumulating $M$ data symbols. Thus, estimation error can vanish through sufficient accumulation even while symbol recovery remains highly unreliable. Numerical results validate the proposed method, demonstrating substantially higher target detection probabilities than pilot-only and hard-decision-based bistatic ranging under the same low-SNR conditions.