High precision hybrid RF and ultrasonic chirp-based ranging for low-power IoT nodes

Hybrid acoustic-RF systems offer excellent ranging accuracy, yet they typically come at a power consumption that is too high to meet the energy constraints of mobile IoT nodes. We combine pulse compression and synchronized wake-ups to achieve a ranging solution that limits the active time of the nodes to 1 ms. Hence, an ultra low-power consumption of 9.015 µW for a single measurement is achieved. The operation time is estimated on 8.5 years on a CR2032 coin cell battery at a 1 Hz update rate, which is over 250 times larger than state-of-the-art RF-based positioning systems. Measurements based on a proof-of-concept hardware platform show median distance error values below 10 cm. Both simulations and measurements demonstrate that the accuracy is reduced at low signal-to-noise ratios and when reflections occur. We introduce three methods that enhance the distance measurements at a low extra processing power cost. Hence, we validate in realistic environments that the centimeter accuracy can be obtained within the energy budget of mobile devices and IoT nodes. The proposed hybrid signal ranging system can be extended to perform accurate, low-power indoor positioning

Static and dynamic evaluations of acoustic positioning system using TDMA and FDMA for robots operating in a greenhouse

Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy, low cost, and ability of extensive greenhouse coverage. Spread Spectrum Sound-based local positioning system (SSSLPS) was proposed to be a navigation tool for multiple agricultural robots by the authors' research team. However, to increase the system capacity for positioning multiple robots in a greenhouse, the near-far problem caused by the interference between speakers needs to be overcome. The use of different access methods, Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA), is essential in the SSSLPS system for solving the near-far problem. The static positioning in a greenhouse was first evaluated by setting different parameters to determine the optimal signal setting for a dynamic experiment. From that, the moving robot tests were added with a motion capture system and tested the performance of TDMA and FDMA. The results demonstrated that TDMA can be used in a stationary sound-based positioning system with 12.2 mm accuracy, but it has a time delay problem in dynamic positioning. A simulation was designed to mimic the position error increases with different moving speeds. Although FDMA has the sound damping problem in high-frequency regions creating a peak detection issue, it achieved a higher accuracy with an average position error of 62.1 mm compared to 180.3 mm of TDMA. This study shows that the TDMA method is suitable for static measurements, while the FDMA method is suitable for measuring dynamic objects and controlling mobile robots

A Hybrid Indoor Location Positioning System

Indoor location positioning techniques have experienced impressive growth in recent years. A wide range of indoor positioning algorithms has been developed for various applications. In this work a practical indoor location positioning technique is presented which utilizes off-the-shelf smartphones and low-cost Bluetooth Low Energy (BLE) nodes without any further infrastructure. The method includes coarse and fine modes of location positioning. In the coarse mode, the received signal strength (RSS) of the BLE nodes is used for location estimation while in the fine acoustic signals are utilized for accurate positioning. The system can achieve centimeter-level positioning accuracy in its fine mode. To enhance the system’s performance in noisy environments, two digital signal processing (DSP) algorithms of (a) band-pass filtering with audio pattern recognition and (b) linear frequency modulated chirp signal with matched filter are implemented. To increase the system’s robustness in dense multipath environments, a method using data clustering with sliding window is employed. The received signal strength of BLE nodes is used as an auxiliary positioning method to identify the non-line-of-sight (NLoS) propagation paths in the acoustic positioning mode. Experimental measurement results in an indoor area of 10 m2 indicate that the positioning error falls below 6 cm

Indoor Positioning Using Acoustic Pseudo-Noise Based Time Difference of Arrival

The Global Positioning System (GPS) provides good precision on a global scale, but is not suitable for indoor applications. Indoor positioning systems (IPS) aim to provide high precision position information in an indoor environment. IPS has huge market opportunity with a growing number of commercial and consumer applications especially as Internet of Things (IoT) develops. This paper studies an IPS approach using audible sound and pseudo-noise (PN) based time difference of arrival (TDoA). The system’s infrastructure consists of synchronized speakers. The object to be located, or receiver, extracts TDoA information and uses multilateration to calculate its position. The proposed IPS utilizes sound waves since they travel much slower compared to electromagnetic waves, allowing for easier measurements. Additionally, the audible spectrum has a large availability of low directivity speakers and microphones allowing for a large coverage area compared to highly directive ultrasonic transceivers. This paper experimentally evaluates the feasibility of the proposed IPS

Acoustic indoor localization employing code division multiple access

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2010Includes bibliographical references (leaves: 107-108)Text in English; Abstract: Turkish and Englishxvi, 160 69 leavesIndoor localization becomes a demand that comes into prominence day by day. Although extensively used outdoor location systems have been proposed, they can not operate in indoor applications. Hence new investigations have been carried on for accurate indoor localization in the last decade. In this thesis, a new indoor location system, that aims to locate an entity within an accuracy of about 2 cm using ordinary and inexpensive off-the-shelf devices, has been proposed and an implementation has been applied to evaluate the system performance. Therefore, time of arrival measurements of acoustic signals, which are binary phase shift keying modulated Gold code sequences using direct sequence spread spectrum technique, are done. Direct sequence-code division multiple access is applied to perform simultaneous accurate distance measurements and provides immunity to noise and interference. Two methods have been proposed for the location estimation. The first method takes the average of four location estimates obtained by trilateration technique. In the second method, only a single robust position estimate is obtained using three distances while the least reliable fourth distance measurement is not taken into account. The system performance is evaluated at positions from two height levels using two sets of variables determined by experimental results. The precision distributions in the work area and the precision versus accuracy plots depict the system performance for different sets of variables. The proposed system provides location estimates of better than 2 cm accuracy within 99% precision. Eventually, created graphical user interface provides a user friendly environment to adjust the parameters

Blind as a bat: audible echolocation on small robots

For safe and efficient operation, mobile robots need to perceive their environment, and in particular, perform tasks such as obstacle detection, localization, and mapping. Although robots are often equipped with microphones and speakers, the audio modality is rarely used for these tasks. Compared to the localization of sound sources, for which many practical solutions exist, algorithms for active echolocation are less developed and often rely on hardware requirements that are out of reach for small robots. We propose an end-to-end pipeline for sound-based localization and mapping that is targeted at, but not limited to, robots equipped with only simple buzzers and low-end microphones. The method is model-based, runs in real time, and requires no prior calibration or training. We successfully test the algorithm on the e-puck robot with its integrated audio hardware, and on the Crazyflie drone, for which we design a reproducible audio extension deck. We achieve centimeter-level wall localization on both platforms when the robots are static during the measurement process. Even in the more challenging setting of a flying drone, we can successfully localize walls, which we demonstrate in a proof-of-concept multi-wall localization and mapping demo.Comment: 8 pages, 10 figures, published in IEEE Robotics and Automation Letter

IMPACT OF MICROPHONE POSITIONAL ERRORS ON SPEECH INTELLIGIBILITY

The speech of a person speaking in a noisy environment can be enhanced through electronic beamforming using spatially distributed microphones. As this approach demands precise information about the microphone locations, its application is limited in places where microphones must be placed quickly or changed on a regular basis. Highly precise calibration or measurement process can be tedious and time consuming. In order to understand tolerable limits on the calibration process, the impact of microphone position error on the intelligibility is examined. Analytical expressions are derived by modeling the microphone position errors as a zero mean uniform distribution. Experiments and simulations were performed to show relationships between precision of the microphone location measurement and loss in intelligibility. A variety of microphone array configurations and distracting sources (other interfering speech and white noise) are considered. For speech near the threshold of intelligibility, the results show that microphone position errors with standard deviations less than 1.5cm can limit losses in intelligibility to within 10% of the maximum (perfect microphone placement) for all the microphone distributions examined. Of different array distributions experimented, the linear array tends to be more vulnerable whereas the non-uniform 3D array showed a robust performance to positional errors