Dispersive frequency-swept interferometry for computationally-efficient ranging

Frequency-modulated continuous-wave (FMCW) ranging enables micron-level precision over tens of meters but suffers from prohibitive latency due to the inherently sequential nature of conventional frequency estimation methods. To address this, we propose a dispersive frequency-swept interferometry approach that converts femtosecond time delays into measurable optical frequency shifts via dispersive modulation, yielding submicrometer computational resolution. Building on this mechanism, we propose a full-range adaptive frequency-shifted cross-correlation (AFS-CC) algorithm that fundamentally decouples the critical path in conventional algorithms by offloading their sequential dependency chain to the physical layer via this dispersion. Furthermore, the spectral sparsity of the modulated signals enables the compression of the dataset from N to N in the final stage, facilitating L2 cache access optimization. This hierarchical design shortens the critical path to approach a single parallel batched FFT. On graphics processing units, AFS-CC achieves speedups of 3.0× and 6.5× over the Chirp-Z Transform and q-Shift estimator methods, respectively, within the bandwidth-bound regime. Experimental results demonstrate a standard deviation below 2.0 µm for a 9.0 m target at 4 pW return power and a bias below 0.7 µm relative to a reference interferometer, with an expanded uncertainty of 1.44 µm+1.25 µm/m⋅R (k=2). This work resolves the efficiency bottlenecks of conventional FMCW systems, enabling high-speed, micron-precision light detection and ranging (LiDAR).