Aiming at the problem that the dynamic change of the scattering environment affects the propagation distance estimation performance by different light sources, resulting in low positioning accuracy and poor robustness, a light quantum positioning method based on integrated coincidence counting and adaptive light source selection is proposed. Specifically, the method considers the dynamic changes of the scattering environment to group the entangled light time pulse sequences, calculates the signal propagation distance of each light source under each group based on the coincidence count, and takes the relative error of each light source under each group as the basis to dynamically select different light sources for positioning. The experimental results show that the proposed method has higher positioning accuracy and stronger positioning robustness.
Aiming at the problem that the dynamic change of the scattering environment affects the propagation distance estimation performance by different light sources, resulting in low positioning accuracy and poor robustness, a light quantum positioning method based on integrated coincidence counting and adaptive light source selection is proposed. Specifically, the method considers the dynamic changes of the scattering environment to group the entangled light time pulse sequences, calculates the signal propagation distance of each light source under each group based on the coincidence count, and takes the relative error of each light source under each group as the basis to dynamically select different light sources for positioning. The experimental results show that the proposed method has higher positioning accuracy and stronger positioning robustness.
Quantum positioning is based on quantum signals to realize target detection. However, the quantum signal is inevitably interfered by the scattering environment during transmission, and the interference changes with the time and transmission path from each Light Source (LS) to the target. It is thereby needed to build up a good strategy for finding the set of the most useful LSs for quantum positioning. Therefore, we propose an entangled quantum positioning method based on the Scattering Free Path (SFP) model. Firstly, the light quantum transmission model is established to describe the change of photon number and transmission distance of the photon. Secondly, the SFP for each LS and each time group is constructed based on environment information and coincidence counting. Thirdly, the SFP sequence for each LS is resampled, and the relative SFP error under each time group is calculated. Finally, the LSs corresponding to the minimum relative errors are selected for each time group to estimate the position coordinate of the target.
As one of the state-of-the-art technologies currently being studied in the field of target positioning, the entangled light quantum-based passive target positioning method uses quantum entangled states to detect and localize the target, thus providing highly-accurate and anti-interference positioning services. The conventional methods seldom consider the problem that maybe a pseudo-target is detected when there is actually no target due to the interference of particles, scatterers, and noise photons during light quantum transmission. To address this problem, this paper proposes a new passive target positioning method on uncertain detection path based on entangled light quantum. Specifically, first of all, by converting the continuous light energy into the discrete photon number, the photon return rate is used to calculate the number of arrival photons based on the counting characteristics of the single photon detector. Second, the detection probabilities of signal, idler, and noise photons are calculated to obtain the coincidence probability at the receiver. Third, according to the coincidence count value of the entangled light time pulse sequence, the Constant False Alarm Rate (CFAR) detection model is established, and the corresponding detection threshold is adaptively adjusted with the change of the background noise to achieve highly-sensitive target detection. Finally, the relative error for each light source is considered to select the optimal light sources with the smallest relative distance errors for target positioning. In addition, the results show that the detection probability of the proposed method is over 95% with the false alarm probability 0.05, the positioning error is centimeter-level, and the confidence probability within 2.60 cm can reach 92%.
In recent years, quantum information technology, as a subversive and strategic technology that has attracted much attention, acquires, transmits, and processes information by means of unique physical phenomena such as quantum entanglement, nonlocality, and non-cloning. Quantum imaging technology achieves non-local imaging of targets by extracting entangled light quantum information with temporal and spatial correlation characteristics. By using the anti-interference and anti-turbulence characteristics of quantum entangled states, quantum imaging technology can break through the physical limits of traditional imaging fields, thereby improving imaging resolution and sensitivity. The latest technological development in quantum imaging has prompted researchers to study high-resolution and fast quantum imaging based on the spatial correlation characteristics of entangled photon pairs. In this circumstance, we propose a novel quantum imaging method based on two-step adaptive sampling optimization and carry out experimental verification. In concrete terms, in order to solve the problem that the efficiency of entangled light quantum imaging is limited by Digital Micromirror Device (DMD) sampling, we select the two-step adaptive sampling optimization algorithm to reduce the influence of DMD scanning on imaging efficiency. At the same time, for the sake of solving the problem that the quality of entangled photon quantum imaging is limited by the accuracy of coincidence counting, we add delay difference calculation in the imaging process and correct the signal photon arrival time pulse sequence to ensure the accuracy of coincidence counting. Finally, we conduct a large number of experiments to evaluate the performance of the two-step adaptive sampling optimization algorithm and verify the superiority of the proposed entangled quantum imaging method practically.
Precise positioning is a key factor and enabler technology for many use cases on intelligent transportation systems (ITS) and connected and automated vehicles (CAVs). Recently, the quantum positioning system (QPS) based on quantum ranging has emerged as a novel way to improve security and precision. As a key process of QPS, the entangled photons based ranging technology has picosecond-level clock synchronization, and the ranging accuracy can reach the Heisenberg limit. If promising QPS is deployed in the ITS and CAVs, it will cause a profound change. However, the existing QPS still lacks accuracy and robustness in different scenarios. To solve this problem, we proposed an efficient and robust fusion positioning system based on entangled photons. In this system, we derive the ranging accuracy limit with many factors and propose a fast data grouping and selection algorithm to improve real-time performance. Furthermore, we propose a fusion extended fingerprint localization method for robust positioning in the dynamic environment. The effectiveness and robustness of the system are verified by extensive experiments. When the range is 15m, the ranging accuracy can be limited to 0.0018m. The proposed system achieves the probability of positioning errors 90% within 0.13m with only two APs.
Recently, ranging has played an increasingly important role in many scenarios, but the problems of limited security and accuracy have always been troubling. The entanglement ranging method provides picosecond-level clock synchronization and unconditional security and is deemed a good solution to meet the growing demand for accuracy and security, promising to play a significant role in the next generation of navigation. This paper focuses on the ranging system based on entangled photons, and proposes solutions to the challenges of accuracy and robustness. Specifically, a coincidence counting calibration algorithm is proposed to suppress the background noise, and a novel data selection algorithm based on relative quantum efficiency is proposed to suppress abnormal coincidence counting. Then, to improve the ranging accuracy even in challenging scenarios, the paper proposed a novel density-based hierarchical filtering algorithm to detect and filter outliers, resulting in more precise and reliable ranging. Finally, extensive experiments are carried out on the built test platform to verify the safety and effectiveness of the proposed system. The results show that the ranging error is 0.0225 m in the test time of 1 ns. The proposed algorithm reduced the ranging error of abnormal data from 1.5205 m to 0.0100 m, and achieved the probability (90%) of ranging error within 0.0150 m.
In order to reduce the time overhead of quantum imaging, a new ranging-assisted quantum imaging method based on coincidence counting is proposed in this paper. Firstly, the Digital Micromirror Device (DMD) is used to select the ranging area in the imaging area, and photon arrival time sequences on signal and reference light paths are recorded by delay coincidence. Secondly, the second-order correlation curve is drawn according to the coincidence count values to obtain the delay difference of these two optical paths. This delay difference corrects the photon arrival time sequences corresponding to the imaging area. Finally, the coincidence counting is performed based on the corrected time sequences, and the quantum imaging result is obtained according to the coincidence count values. Experimental results show that the proposed method can greatly reduce the time overhead of quantum imaging.