1,016 research outputs found
Understanding and ameliorating non-linear phase and amplitude responses in AMCW Lidar
Amplitude modulated continuous wave (AMCW) lidar systems commonly suffer from non-linear phase and amplitude responses due to a number of known factors such as aliasing and multipath inteference. In order to produce useful range and intensity information it is necessary to remove these perturbations from the measurements. We review the known causes of non-linearity, namely aliasing, temporal variation in correlation waveform shape and mixed pixels/multipath inteference. We also introduce other sources of non-linearity, including crosstalk, modulation waveform envelope decay and non-circularly symmetric noise statistics, that have been ignored in the literature. An experimental study is conducted to evaluate techniques for mitigation of non-linearity, and it is found that harmonic cancellation provides a significant improvement in phase and amplitude linearity
A New Vehicle Localization Scheme Based on Combined Optical Camera Communication and Photogrammetry
The demand for autonomous vehicles is increasing gradually owing to their
enormous potential benefits. However, several challenges, such as vehicle
localization, are involved in the development of autonomous vehicles. A simple
and secure algorithm for vehicle positioning is proposed herein without
massively modifying the existing transportation infrastructure. For vehicle
localization, vehicles on the road are classified into two categories: host
vehicles (HVs) are the ones used to estimate other vehicles' positions and
forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV
transmits modulated data from the tail (or back) light, and the camera of the
HV receives that signal using optical camera communication (OCC). In addition,
the streetlight (SL) data are considered to ensure the position accuracy of the
HV. Determining the HV position minimizes the relative position variation
between the HV and FV. Using photogrammetry, the distance between FV or SL and
the camera of the HV is calculated by measuring the occupied image area on the
image sensor. Comparing the change in distance between HV and SLs with the
change in distance between HV and FV, the positions of FVs are determined. The
performance of the proposed technique is analyzed, and the results indicate a
significant improvement in performance. The experimental distance measurement
validated the feasibility of the proposed scheme
Modeling and Compensating of Noise in Time-of-Flight Sensors
Three-dimensional (3D) sensors provide the ability to perform contactless measurements of objects and distances that are within their field of view. Unlike traditional two-dimensional (2D) cameras, which only provide RGB data about objects within a scene, 3D sensors are able to directly provide depth information for objects within a scene. Of these 3D sensing technologies, Time-of-Flight (ToF) sensors are becoming more compact which allows them to be more easily integrated with other devices and to find use in more applications. ToF sensors also provide several benefits over other 3D sensing technologies that increase the types of applications where ToF sensors can be used. For example, over the last decade, ToF sensors have become more widely used in applications such as 3D scanning, drone positioning, robotics, logistics, structural health monitoring, and road surveillance. To further extend the applications where ToF sensors can be employed, this work focuses on how to improve the performance of ToF sensors by suppressing and mitigating the effects of noise artifacts that are associated with ToF sensors. These issues include multipath interference, motion blur, and multicamera interference in 3D depth maps and point clouds
Digital Signal Processing for Optical Communications and Coherent LiDAR
Internet data traffic within data centre, access and metro networks is experiencing
unprecedented growth driven by many data-intensive applications. Significant
efforts have been devoted to the design and implementation of low-complexity
digital signal processing (DSP) algorithms that are suitable for these short-reach
optical links. In this thesis, a novel low-complexity frequency-domain (FD)
multiple-input multiple-output (MIMO) equaliser with momentum-based gradient
descent algorithm is proposed, capable of mitigating both static and dynamic
impairments arising from the optical fibre. The proposed frequency-domain
equaliser (FDE) also improves the robustness of the adaptive equaliser against
feedback latencies which is the main disadvantage of FD adaptive equalisers under
rapid channel variations.
The development and maturity of optical fibre communication techniques over
the past few decades have also been beneficial to many other fields, especially
coherent light detection and ranging (LiDAR) techniques. Many applications
of coherent LiDAR are also cost-sensitive, e.g., autonomous vehicles (AVs).
Therefore, in this thesis, a low-cost and low-complexity single-photodiode-based
coherent LiDAR system is investigated. The receiver sensitivity performance of this
receiver architecture is assessed through both simulations and experiments, using
two ranging waveforms known as double-sideband (DSB) amplitude-modulated
chirp signal and single-sideband (SSB) frequency-modulated continuous-wave
(FMCW) signals. Besides, the impact of laser phase noise on the ranging precision
when operating within and beyond the laser coherence length is studied. Achievable
ranging precision beyond the laser coherence length is quantified
Automotive Three-Dimensional Vision Through a Single-Photon Counting SPAD Camera
We present an optical 3-D ranging camera for automotive applications that is able to provide a centimeter depth resolution over a mbox{40}^{\circ} \times mbox{20}^{\circ} field of view up to 45 m with just 1.5 W of active illumination at 808 nm. The enabling technology we developed is based on a CMOS imager chip of 64 \times 32 pixels, each with a single-photon avalanche diode (SPAD) and three 9-bit digital counters, able to perform lock-in time-of-flight calculation of individual photons emitted by a laser illuminator, reflected by the objects in the scene, and eventually detected by the camera. Due to the SPAD single-photon sensitivity and the smart in-pixel processing, the camera provides state-of-the-art performance at both high frame rates and very low light levels without the need for scanning and with global shutter benefits. Furthermore, the CMOS process is automotive certified
Identification and Mitigation of NLOS based on Channel Information Rules for Indoor UWB Localization
Indoor localization is an emerging technology that can be utilized for developing products and services for commercial usage, public safety, military applications and so forth. Commercially it can be applied to track children, people with special needs, help navigate blind people, locate equipment, mobile robots, etc. The objective of this thesis is to enable an indoor mobile vehicle to determine its location and thereby making it capable of autonomous localization under Non-light of sight (NLOS) conditions. The solution developed is based on Ultra Wideband (UWB) based Indoor Positioning System (IPS) in the building. The proposed method increases robustness, scalability, and accuracy of location. The out of the box system of DecaWave TREK1000 provides tag tracking features but has no method to detect and mitigate location inaccuracies due to the multipath effect from physical obstacles found in an indoor environment. This NLOS condition causes ranges to be positively biased, hence the wrong location is reported. Our approach to deal with the NLOS problem is based on the use of Rules Classifier, which is based on channel information. Once better range readings are achieved, approximate location is calculated based on Time of Flight (TOF). Moreover, the proposed rule based IPS can be easily implemented on hardware due to the low complexity. The measurement results, which was obtained using the proposed mitigation algorithm, show considerable improvements in the accuracy of the location estimation which can be used in different IPS applications requiring centimeter level precision. The performance of the proposed algorithm is evaluated experimentally using an indoor positioning platform in a laboratory environment, and is shown to be significantly better than conventional approaches. The maximum positioning error is reduced to 15 cm for NLOS using both an offline and real time tracking algorithm extended from the proposed approach
Wi-Fi Sensing for Indoor Localization via Channel State Information: A Survey
Wireless Fidelity (Wi-Fi) sensing utilization has been widespread, especially for human behavior/activity recognition. It provides high flexibility since it does not require the person/object to carry any device known as device-free. This "passive" concept is also helpful for another application of Wi-Fi sensing, i.e., indoor localization. The "sensing" is conducted using particular parameters extracted from communication links of Wi-Fi devices, i.e., channel state information (CSI). This paper explores the recent trends in CSI-based indoor localization with Wi-Fi technology as its core, including their advantages, challenges, and future directions. We found tremendous benefits can be gained by employing Wi-Fi sensing in localization supported by its performance and integrability for other intelligent systems for activity recognition
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