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In this paper, we present the design of a proposed optical rangefinder to determine the distance of a semi-reflective target from the sensor module. The sensor module deploys a simple Tunable Focus Lens (TFL), a Laser Source (LS) with a Gaussian Beam profile and a digital beam profiler/imager to achieve its desired operation. We show that, owing to the nature of existing measurement methodologies, previous attempts to use a simple TFL in prior art to estimate target distance mostly deliver “one-shot” distance measurement estimates instead of obtaining and using a larger dataset which can significantly reduce the effect of some largely incorrect individual data points on the final distance estimate. Using a measurement dataset and calculating averages also helps smooth out measurement errors in individual data points through effectively low-pass filtering unexpectedly odd measurement offsets in individual data points. In this paper, we show that a simple setup deploying an LS, a TFL and a beam profiler or imager is capable of delivering an entire measurement dataset thus effectively mitigating the effects on measurement accuracy which are associated with “one-shot” measurement techniques. The technique we propose allows a Gaussian Beam from an LS to pass through the TFL. Tuning the focal length of the TFL results in altering the spot size of the beam at the beam imager plane. Recording these different spot radii at the plane of the beam profiler for each unique setting of the TFL provides us with a means to use this measurement dataset to obtain a significantly improved estimate of the target distance as opposed to relying on a single measurement. We show that an iterative least-squares curve-fit on the recorded data allows us to estimate distances of remote objects very precisely. We also show that using some basic ray-optics-based approximations, we also obtain an initial seed value for distance estimate and subsequently use this value to obtain a more precise estimate through an iterative residual reduction in the least-squares sense. In our experiments, we use a MEMS-based Digital Micro-mirror Device (DMD) as a beam imager/profiler as it delivers an accurate estimate of a Gaussian Beam profile. The proposed method, its working and the distance estimation methodology are discussed in detail. For a proof-of-concept, we back our claims with initial experimental results.

Various existing target ranging techniques are limited in terms of the dynamic range of operation and measurement resolution. These limitations arise as a result of a particular measurement methodology, the finite processing capability of the hardware components deployed within the sensor module, and the medium through which the target is viewed. Generally, improving the sensor range adversely affects its resolution and vice versa. Often, a distance sensor is designed for an optimal range/resolution setting depending on its intended application. Optical triangulation is broadly classified as a spatial-signal-processing-based ranging technique and measures target distance from the location of the reflected spot on a position sensitive detector (PSD). In most triangulation sensors that use lasers as a light source, beam divergence-which severely affects sensor measurement range-is often ignored in calculations. In this paper, we first discuss in detail the limitations to ranging imposed by beam divergence, which, in effect, sets the sensor dynamic range. Next, we show how the resolution of laser-based triangulation sensors is limited by the interpixel pitch of a finite-sized PSD. In this paper, through the use of tunable focus lenses (TFLs), we propose a novel design of a triangulation-based optical rangefinder that improves both the sensor resolution and its dynamic range through adaptive electronic control of beam propagation parameters. We present the theory and operation of the proposed sensor and clearly demonstrate a range and resolution improvement with the use of TFLs. Experimental results in support of our claims are shown to be in strong agreement with theory.