Non-line-of-sight (NLOS) positioning technology has become an important research direction in the field of emergency response, as it can overcome line-of-sight limitations and achieve target positioning in obstructed scenarios. The core of the technology lies in the extraction accuracy of the photon flight time. However, existing methods exhibit deficiencies in extraction accuracy, limiting their application in complex environments. Moreover, current quantum-based positioning technologies fail to consider positioning performance under target occlusion. The coincidence counting method, while being fundamental for obtaining photon time-of-flight (ToF) in quantum techniques, suffers from high computational overhead that restricts practical efficiency. To address these challenges, this paper proposes a NLOS ToF positioning method based on coincidence count optimization.

This paper proposes a NLOS ToF positioning method based on coincidence count optimization. The system framework of the proposed method is illustrated in Fig. 1. First, entangled photon pairs are generated through the spontaneous parametric down-conversion (SPDC) process in a nonlinear crystal, providing a stable signal source for the positioning system. Next, based on the NLOS photon transmission model, a correlation-based photon selection algorithm is employed to identify entangled pairs. This algorithm records photon arrival timestamps using single-photon detectors (SPDs), obtains preliminary photon ToF through coincidence counting, and improves ToF accuracy by filtering out uncorrelated photon pairs according to the time-correlation characteristics. In the final stage, the optimized photon ToF information is combined with a back-projection algorithm to achieve high-precision positioning in NLOS environments.

When the ToF extraction error is 0.045 ns, the cumulative probabilities for raw unprocessed data, Gaussian filtering, median filtering, and wavelet filtering are 14.10%, 21.61%, 16.54%, and 12.11% respectively. In contrast, the quantum coincidence counting reaches 90.42% probability through photon-pair correlation filtering (Fig. 7). To assess ToF method robustness, light path length varies from 10 to 22 m across 7 surface points. As the light path length increases, photon loss during propagation reduces SPD counts, increasing ToF errors in both conventional and coincidence methods. Gaussian filtering shows an error increase from 0.05 to 0.32 ns, while median filtering shows an increase from 0.043 to 0.44 ns, and wavelet filtering from 0.07 to 0.23 ns. In contrast, the quantum coincidence counting method demonstrates superior robustness, with its time error only increasing from 0.01 to 0.09 ns. This enhanced performance is attributed to the method’s effective utilization of strong quantum correlations between entangled photon pairs (Fig. 8). Furthermore, with 5×10? photon arrival events, the quantum coincidence counting method requires 750 s of computational time at its optimal 250 ps window width, whereas the proposed method maintains computational costs below 9 s across all window widths [Fig. 10(b)]. Under a 600 ps coincidence window width, with 5×10? photon arrival events, quantum coincidence counting requires approximately 413 s for timestamp processing. The proposed method reduces this to just 5 s by filtering uncorrelated photons [Fig. 11(a)]. Finally, when the scanning point combination is A, B, C, and D, the ToF resolution performance of all methods deteriorates due to small relative distances between the points. The proposed method achieves horizontal, vertical and total errors of 0.012 m, 0.054 m, and 0.066 m, respectively, whereas the corresponding errors for the quantum coincidence counting method are 0.078 m, 0.141 m, and 0.219 m. When the scanning points are changed to C, D, F, and G, the extended light path reduces signal photons and increases noise. The total positioning errors for Gaussian filtering, median filtering, wavelet filtering, and quantum coincidence counting rise significantly to 1.27, 1.28, 1.80, and 0.04 m, respectively (Fig. 14). The proposed method attains a 90% confidence probability within a positioning error of 0.25 m, while the quantum coincidence counting method requires an error margin of 0.5 m to reach the same confidence level. In comparison, Gaussian filtering achieves 89.56% confidence at 3.25 m, while median filtering reaches 89.3% at 6.5 m, and wavelet filtering attains 95.4% at 8.25 m (Fig. 15).

To address the positioning accuracy degradation caused by low-precision photon ToF extraction, we propose a NLOS ToF positioning method based on coincidence count optimization. First, the second-order correlation properties of entangled photon pairs are utilized to obtain high-precision ToF through coincidence counting. Then, to mitigate the high computational overhead associated with quantum coincidence counting methods, entangled photon pair selection algorithm based on time correlation is proposed, which effectively reduces the time consumption of coincidence counting while maintaining timing accuracy. Finally, precise NLOS positioning is achieved using the optimized photon ToF. Experimental results demonstrate that the proposed method achieves a timing error of 12.75 ps at a coincidence window width of 350 ps, enabling NLOS positioning with an error of 1.2 cm.