Single-photon time-of-flight light detection and ranging (LiDAR) is a versatile technique for the measurement of absolute distances and for depth profiling. It has a wide variety of applications (e.g., land surveying, autonomous car navigation, underwater imaging) with the potential to achieve high-resolution three-dimensional images over long ranges when the key components of the measurement system are of a suitably high specification. In this work, a novel, high-efficiency, and low timing jitter superconducting nanowire single-photon detector, in conjunction with a custom single-pixel scanning transceiver system, and the time-correlated single-photon counting technique, enable the acquisition of millimeter-scale resolution depth images of scenes at standoff distances of hundreds of meters. A 1550 nm wavelength fiber laser was coupled to the monostatic transceiver to provide the illumination. The system was eye-safe with the maximum average optical output power being ≤3.5mW for measurements of a scene at a standoff distance of 1 km. The overall system instrumental response was approximately 13 ps full width half maximum. This enabled 1 mm depth features on a reference board and a human head to be clearly resolved when measured by the system in broad daylight at standoff distances of 45 and 325 m using per-pixel acquisition times of between 0.25 and 1 ms. These high-resolution results demonstrate the enormous potential of such a system to acquire detailed depth and intensity images of scenes from long distances in daylight or darkness conditions. This could lead to step change improvements in applications such as facial and human activity recognition and the imaging of scenes through clutter and atmospheric obscurants.

Time-of-flight Lidars based on single-photon avalanche diode (SPAD) detector arrays are emerging as a strong candidate technology for long range three-dimensional imaging in challenging environmental conditions. However, reaching this bound requires the existence of an unbiased estimator, which does not necessarily exist for data acquired by realistic SPAD-based Lidar systems. Here, we extend our existing SPAD Lidar modelling framework to include a novel metric, which we term the ‘Binomial Separation Criterion’, as a means of quantifying whether a depth estimation algorithm will reach the Cramér-Rao bound (CRB). This enables us to evaluate the performance of SPAD Lidar systems over a significantly larger state space range than previously, i.e., evaluation in scenarios where the total number of measured photons and peak signal-to-noise ratio change by an order of magnitude. We validate this new approach against data acquired from two separate depth imaging systems, one operating at 532 nm and one at 1550 nm wavelengths, measuring targets at a range of 1.4 km. We present strong agreements between the outputs of our framework and the experimental results across different operating wavelengths, spatial resolutions, target types, and sensor architectures. We expect this framework to serve as a highly versatile tool with wide-ranging applicability to the SPAD Lidar community.

Commonly, accelerometers are used to determine the tension force in cables through an indirect process; however, it is necessary to know the mechanical parameters of each element, such as mass and length. Typically, obtaining or measuring these parameters is not feasible. Therefore, this research proposed an alternative methodology to indirectly estimate them based on historical information about the so-called classic instruments (accelerometers and hydraulic jack). This case study focused on the Rio Papaloapan Bridge located in Veracruz, Mexico, a structure that has experienced material casting issues due to inadequate heat treatment in some cable top anchor over its lifespan. Thirteen cables from the structure were selected to evaluate the proposed methodology, yielding results within 3.8% of difference compared to direct tension estimation generated by a hydraulic jack. Furthermore, to enhance data collection, this process was complemented using a computer vision methodology. This involved remotely measuring the vibration frequency of cables from high-resolution videos recorded with a smartphone. The non-contact method was validated in a laboratory using a vibrating table, successfully estimating oscillation frequencies from video-recording with a fixed camera. A field test on eight cables of a bridge was also conducted to assess the performance and feasibility of the proposed method. The results demonstrated an RMS Error of approximately 2 mHz and a percentage difference in the tension force estimation below 3% compared to an accelerometer measurement approach. Finally, it was determined that this composed methodology for indirect tension force determination is a viable option when: (1) cables are challenging to access; (2) there is no line of sight between the camera and cables outside the bridge; (3) there is a lack of information about the mechanical parameters of the cables.

Picosecond resolution time-correlated mode has emerged as a candidate technology for a variety of depth imaging applications in the visible, near-infrared and short-wave infrared regions. This presentation will examine this approach in a range of challenging sensing scenarios including: imaging though highly scattering underwater conditions; free-space imaging through obscurants such as smoke or fog; and depth imaging of complex scenes containing multiple surfaces.