Rohan Kapoor

This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on performance modeling and the system layout. Acoustic transmitters are arranged at known fixed locations and broadcast their respective signals following a Time Division Multiple Access (TDMA) scheme. The receiver position is calculated based on Time of Arrival (TOA) based ranging measurements from a minimum of four transmitters. The transmitters are arranged optimally to minimize Position Dilution of Precision (PDOP) as well as maximizing sensor availability. The proposed technique can provide accurate navigation observables in indoor environments, where conventional satellite-based navigation systems cannot deliver the required Position, Velocity, and Time (PVT) data. Additionally, being based on acoustic signals, it is immune to signal-in-space electromagnetic interferences. The TDMA based acoustic navigation system is described, with potential errors in ranging due to Doppler effect, multipath, atmospheric propagation, and signal delays. The error in positioning due to platform dynamics is also discussed. This analysis will lead to an optimized arrangement of transmitters supporting the future ground and flight experimental activities.

This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on performance modelling and the system layout optimisation. Acoustic transmitters are arranged at known fixed locations and broadcast their respective signals following a Time Division Multiple Access (TDMA) scheme. The receiver position is calculated based on ranging measurements from a minimum of four transmitters. The range is calculated based on time-of-flight (TOF) of acoustic waves from the transmitter to the receiver. The transmitters are arranged optimally to minimize Position Dilution of Precision (PDOP). Optimizing the location of transmitters for minimum PDOP also leads to better coverage in the indoor environment, where conventional satellite based navigation systems cannot deliver the required Position, Velocity and Time (PVT) data. The attenuation of sound in air is discussed along with potential ranging errors and signal delays. Simulations are carried out to optimize the arrangement of transmitters for future experiments with indoor air and surface vehicles.

Animals, especially mammals like bats and dolphins, use acoustic waves that vary in frequency, signal duration, and intensity, for navigation and tracking. The directionality of acoustic waves has also been long used for localization by human beings. The term ‘echolocation’ was coined by Donald R. Griffin, where he discusses ship captains exploiting sound to ascertain the ship's surroundings and avoid obstacles in low-visibility environments. Acoustic sensors can provide a low-cost, size, weight, and power (C-SWaP) navigation solution, which is scalable and robust. Moreover, acoustic sensors have the capability to provide high-resolution spatial information at short distance range. This paper presents a novel acoustic positioning and navigation system for a micro aerial vehicle. Flight tests are performed to evaluate the system, where the performance of the acoustic system is compared with a motion capture system.

Integrated System Health Management (ISHM) is a promising technology that fuses sensor data and historical state-of-health information of components and subsystems to provide actionable information and enable intelligent decision-making regarding the operation and maintenance of aerospace systems. ISHM fundamentally relies on assessments and predictions of system health, including the early detection of failures and estimation of Remaining Useful Life (RUL). Model-based, data-driven or hybrid reasoning techniques can be utilized to maximise the timeliness and reliability of diagnosis and prognosis information. The benefits of ISHM include enhancing the maintainability, reliability, safety and performance of systems. The next evolution of the ISHM concept, Intelligent Health and Mission Management (IHMM), delves deeper into the utilization of on-line system health predictions to modify mission profiles to ensure safety and reliability, as well as efficiency through predictive integrity. This concept is particularly important for Trusted Autonomous System (TAS) applications, where an accurate assessment of the current and future system state-of-health to make operational decisions (with or without human intervention) is integral to both flight safety and mission success. IHMM systems introduce the capability of predicting degradation in the functional performance of subsystems, with sufficient time to dynamically identify which appropriate restorative or reconfiguration actions to take in order to ensure that the system can perform at an acceptable level of operational capability before the onset of a failure event. This paper reviews some of the key advancements and contributions to knowledge in the field of ISHM for the aerospace industry, with a particular focus on various architectures and reasoning strategies involving the use of artificial intelligence. The paper also discusses the key challenges faced in the development and deployment of ISHM systems in the aerospace industry and highlights the safety-critical role that IHMM will play in future cyber-physical and autonomous system applications (both vehicle and ground support systems), such as Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Urban Air Mobility (UAM) and Distributed Satellite Systems (DSS).

This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for Intelligent Transport Systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncer...

The concept of a bio-inspired navigation system using acoustic sensors is presented and various possible approaches for its effective integration in Remotely Piloted Aircraft Systems (UAS) are investigated. Acoustic sensors can have useful applications in UAS obstacle detection and localization, especially in Global Navigation Satellite System (GNSS) denied environments. Taking inspiration from echolocating mammals, especially bats, novel navigation techniques are presented employing both multistatic and monostatic acoustic sensors. Laboratory experiments are presented in which a small array of transmitters provides input data to a multilateration receiver. Based on the positive results of these initial experiments, various possible approaches are investigated for integration of the proposed echolocation techniques in a multi-sensor UAS Navigation and Guidance System (NGS) and in an Acoustic Laser Obstacle Avoidance (ALOA) system for Separation Assurance and Collision Avoidance (SA&...

This paper presents a novel multilateration based sensor grid, using 40 KHz ultrasonic transducers for indoor positioning. Based on time-of-flight of incoming ultrasonic signals, position of autonomous vehicle is calculated. This allows for conducting silent or covert operations. Multilateration theory and algorithm are first described. Laboratory experiments were performed using an array of transmitters set up on the ceiling and the sensor system was tested for position accuracy. Experimental results show the prototype system to have a 1- sigma position error of about 16 cm. This research work lays down foundations for future development of ultrasonic navigation sensors for micro Unmanned Aerial Vehicles (UAVs) in indoor environments.

Current navigation sensors largely rely on electromagnetic signals to obtain position, velocity, and time (PVT) information. However, it can be observed that mammals like bats use acoustic waves, mostly ultrasound, for echolocation and relative navigation/collision avoidance purposes. Acoustic waves are also used by cetaceans like dolphins and sperm whales for echolocation. This paper investigates the performance of a novel acoustic positioning and navigation system (APNS) inspired by nature. Acoustic sensors have relatively lower cost, size, weight, and power (C-SWAP) and are easy to deploy. Additionally, being based on acoustic signals, this technique is immune to signal-in-space electromagnetic interferences. The attenuation of sound in air is discussed along with potential ranging errors and signal delays. A multistatic arrangement of sensors is discussed in detail, with an optimized arrangement of transmitters in a given test geometry. The transmitters broadcast their respectiv...

This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on performance modeling and the system layout. Acoustic transmitters are arranged at known fixed locations and broadcast their respective signals following a Time Division Multiple Access (TDMA) scheme. The receiver position is calculated based on Time of Arrival (TOA) based ranging measurements from a minimum of four transmitters. The transmitters are arranged optimally to minimize Position Dilution of Precision (PDOP) as well as maximizing sensor availability. The proposed technique can provide accurate navigation observables in indoor environments, where conventional satellite-based navigation systems cannot deliver the required Position, Velocity, and Time (PVT) data. Additionally, being based on acoustic signals, it is immune to signal-in-space electromagnetic interferences. The TDMA based acoustic navigation system is described, with potential errors in ranging due to Doppler effect, ...

This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on performance modelling and the system layout optimisation. Acoustic transmitters are arranged at known fixed locations and broadcast their respective signals following a Time Division Multiple Access (TDMA) scheme. The receiver position is calculated based on ranging measurements from a minimum of four transmitters. The range is calculated based on time-of-flight (TOF) of acoustic waves from the transmitter to the receiver. The transmitters are arranged optimally to minimize Position Dilution of Precision (PDOP). Optimizing the location of transmitters for minimum PDOP also leads to better coverage in the indoor environment, where conventional satellite based navigation systems cannot deliver the required Position, Velocity and Time (PVT) data. The attenuation of sound in air is discussed along with potential ranging errors and signal delays. Simulations are carried out to optimize the arrangement of transmitters for future experiments with indoor air and surface vehicles.

This paper addresses one of the recognized barriers to the unrestricted adoption of Unmanned Aircraft (UA) in mainstream urban use—noise—and reviews existing approaches for estimating and mitigating this problem. The aircraft noise problem is discussed upfront in general terms by introducing the sound emission, propagation, and psychoacoustic effects. The propagation of sound in the atmosphere, which is the focus of this paper, is then analysed in detail to isolate the environmental and operational factors that predominantly influence the perceived noise on the ground, especially looking at large-scale low-altitude UA operations, such as in the envisioned Urban Air Mobility (UAM) concepts. The physics of sound propagation are presented, considering all attenuation effects and the anomalies due to Doppler and atmospheric effects, such as wind, thermal inversion, and turbulence. The analysis allows to highlight the limitations of current mainstream aircraft noise modelling and certifi...

Automated collection of on-vehicle sensor data allows the development of artificial intelligence (AI) techniques for vehicular systems’ diagnostic and prognostic processes to better assess the state-of-health, predict faults and evaluate residual life of ground vehicle systems. One of the vital subsystems, in terms of safety and mission criticality, is the power train, (comprising the engine, transmission, and final drives), which provides the driving torque required for vehicle acceleration. In this paper, a novel health and usage monitoring system (HUMS) architecture is presented, together with dedicated diagnosis/prognosis algorithms that utilize data gathered from a sensor network embedded in an armoured personnel carrier (APC) vehicle. To model the drivetrain, a virtual dynamometer is introduced, which estimates the engine torque output for successive comparison with the measured torque values taken from the engine control unit. This virtual dynamometer is also used in conjunct...

This paper addresses some of the existing research gaps in the practical use of acoustic waves for navigation of autonomous air and surface vehicles. After providing a characterisation of ultrasonic transducers, a multistatic sensor arrangement is discussed, with multiple transmitters broadcasting their respective signals in a round-robin fashion, following a time division multiple access (TDMA) scheme. In particular, an optimisation methodology for the placement of transmitters in a given test volume is presented with the objective of minimizing the position dilution of precision (PDOP) and maximizing the sensor availability. Additionally, the contribution of platform dynamics to positioning error is also analysed in order to support future ground and flight vehicle test activities. Results are presented of both theoretical and experimental data analysis performed to determine the positioning accuracy attainable from the proposed multistatic acoustic navigation sensor. In particula...