José Carlos Prieto

PDR with a Foot-Mounted IMU and Ramp Detection

The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.

Improved Heuristic Drift Elimination (iHDE) for pedestrian navigation in complex buildings

The main problem of Pedestrian Dead-Reckoning (PDR) using only a body-attached IMU is the accumulation of heading errors. The heading provided by magnetometers in indoor buildings is in general not reliable. Recently, a new method was proposed called Heuristic Drift Elimination (HDE) that minimizes the heading error when navigating in buildings. It assumes that the majority of buildings have their corridors parallel to each other, or they intersect at right angles, and consequently most of the time the person walks along a straight path with a heading constrained to one of four possible directions. In this paper we study the performance of HDE-based methods in complex buildings, i.e. with pathways also oriented at 45°, long curved corridors, and wide areas where non-oriented motion is possible. We explain how the performance of the original HDE method can be deteriorated in complex buildings. We also propose an improved HDE method called iHDE, that is implemented over a PDR framework that uses foot-mounted inertial navigation with an Extended Kalman Filter (EKF). The EKF is fed with the iHDE-estimated orientation error, as well as the confidence over that correction. We experimentally evaluated the performance of the proposed iHDE-based PDR method, comparing it with the original HDE implementation. Results show that both methods perform very well in ideal orthogonal narrow-corridor buildings, and iHDE outperforms HDE for non-ideal trajectories (e.g. curved paths).

Improved heuristic drift elimination with magnetically-aided dominant directions MiHDE for pedestrian navigation in complex buildings

The main problem of pedestrian dead-reckoning (PDR) using only a body-attached inertial measurement unit is the accumulation of heading errors. The heading provided by magnetometers in indoor buildings is in general not reliable and therefore it is commonly not used. Recently, a new method was proposed called heuristic drift elimination (HDE) that minimises the heading error when navigating in buildings. It assumes that the majority of buildings have their corridors parallel to each other, or they intersect at right angles, and consequently most of the time the person walks along a straight path with a heading constrained to one of the four possible directions. In this article we study the performance of HDE-based methods in complex buildings, i.e. with pathways also oriented at 45°, long curved corridors, and wide areas where non-oriented motion is possible. We explain how the performance of the original HDE method can be deteriorated in complex buildings, and also, how severe errors can appear in the case of false matches with the buildings dominant directions. Although magnetic compassing indoors has a chaotic behaviour, in this article we analyse large data-sets in order to study the potential use that magnetic compassing has to estimate the absolute yaw angle of a walking person. Apart from these analysis, this article also proposes an improved HDE method called Magnetically-aided Improved Heuristic Drift Elimination (MiHDE), that is implemented over a PDR framework that uses foot-mounted inertial navigation with an extended Kalman filter (EKF). The EKF is fed with the MiHDE-estimated orientation error, gyro bias corrections, as well as the confidence over that corrections. We experimentally evaluated the performance of the proposed MiHDE-based PDR method, comparing it with the original HDE implementation. Results show that both methods perform very well in ideal orthogonal narrow-corridor buildings, and MiHDE outperforms HDE for non-ideal trajectories (e.g. curved paths) and also makes it robust against potential false dominant direction matchings.

Optimal placement of sensors for trilateration: regular lattices vs meta-heuristic solutions

Location-aware applications, such as indoor robot navigation or human activity monitoring, require the location estimation of moving elements, by using ultrasonic, infrared or radio signals received from sensors deployed in the workplace. These sensors are commonly arranged in regular lattices on the ceiling. However, this configuration is not optimal for location estimation using trilateration techniques, in terms of positioning precision, maximum coverage and minimum singular cases. This paper shows how non-regular optimal sensor deployments, generated with a new meta-heuristic optimization methodology (Diversified Local Search - DLS), outperforms regular lattices for trilateration.

Compensation of multiple access interference effects in CDMA-based acoustic positioning systems

Recently developed acoustic positioning systems operate in a code division multiple access (CDMA) configuration, in which the ranging signals between the nodes are digitally modulated orthogonal codes with the same carrier frequency and overlapping in time. CDMA permits higher position update rate than the alternative time division multiple access, but suffers from multiple access interference (MAI) effects, leading to outliers in the estimated ranges, and potentially large errors in position estimation. In this communication, we present and demonstrate experimentally a subtractive parallel interference cancelation (PIC) method, which achieves a high degree of resistance to MAI effects, and also permits us to compensate the intersymbol interference (ISI) caused by the limited frequency range of acoustic transducers. When evaluated empirically in an acoustic positioning system, the PIC algorithm obtains nearly total outlier cancelation for four operating beacons, and 2/3 reduction of outliers for a seven beacon setup with 32 bits long codes. Outliers are further reduced (down to 2%) by the modified PIC algorithm with ISI compensation. The method outperforms alternative outlier reduction techniques like doubling or quadrupling the signal length, or using power control to adjust the relative amplitudes of the beacon signals, and permits that the system is available for positioning over 95% of the time.

Airborne ultrasonic vortex generation using flexible ferroelectrets

Cellular ferroelectrets exhibit interesting electromechanical- acoustical characteristics. Their recent appearance and remarkable properties open up new possibilities for the design and development of ultrasonic transducers. In particular, the feasibility of fabricating ultrasonic vortex generators using ferroelectret films is demonstrated in this work. To this end, a transducer prototype was built by gluing the material onto a tangential-helical surface (outer diameter: 40 mm, pitch: 3.45 mm). Experimental results agree well with the theoretical estimation of the pressure and phase of the acoustic field in the near field and far field, which corroborates the potential of ferroelectrets to customize special acoustic fields. Furthermore, the proposed fabrication procedure is inexpensive and represents a new alternative for exploring and analyzing the special characteristics of acoustical helical wavefronts.

Auto-localization algorithm for local positioning systems

This paper studies the problem of determining the position of beacon nodes in Local Positioning Systems (LPSs), for which there are no inter-beacon distance measurements available and neither the mobile node nor any of the stationary nodes have positioning or odometry information. The common solution is implemented using a mobile node capable of measuring its distance to the stationary beacon nodes within a sensing radius. Many authors have implemented heuristic methods based on optimization algorithms to solve the problem. However, such methods require a good initial estimation of the node positions in order to find the correct solution. In this paper we present a new method to calculate the inter-beacon distances, and hence the beacons positions, based in the linearization of the trilateration equations into a closed-form solution which does not require any approximate initial estimation. The simulations and field evaluations show a good estimation of the beacon node positions.

RoPEUS: A New Robust Algorithm for Static Positioning in Ultrasonic Systems.

A well known problem for precise positioning in real environments is the presence of outliers in the measurement sample. Its importance is even bigger in ultrasound based systems since this technology needs a direct line of sight between emitters and receivers. Standard techniques for outlier detection in range based systems do not usually employ robust algorithms, failing when multiple outliers are present. The direct application of standard robust regression algorithms fails in static positioning (where only the current measurement sample is considered) in real ultrasound based systems mainly due to the limited number of measurements and the geometry effects. This paper presents a new robust algorithm, called RoPEUS, based on MM estimation, that follows a typical two-step strategy: 1) a high breakdown point algorithm to obtain a clean sample, and 2) a refinement algorithm to increase the accuracy of the solution. The main modifications proposed to the standard MM robust algorithm are a built in check of partial solutions in the first step (rejecting bad geometries) and the off-line calculation of the scale of the measurements. The algorithm is tested with real samples obtained with the 3D-LOCUS ultrasound localization system in an ideal environment without obstacles. These measurements are corrupted with typical outlying patterns to numerically evaluate the algorithm performance with respect to the standard parity space algorithm. The algorithm proves to be robust under single or multiple outliers, providing similar accuracy figures in all cases.

Robust regression applied to ultrasound location systems

Local positioning systems (LPS), specially those using ultrasound, are able to accurately estimate the location of persons or objects indoors. However, under certain circumstances, its accuracy can be strongly deteriorated by outlying noise. This paper analyzes and compares several strategies for robust trilateration, such as high-breakdown-point robust methodologies, as well as the parity space outlier detection procedure, which is commonly used in GPS. This analysis is performed by simulation in a typical ultrasound location system scenario based on the actual location of nodes in the 3D-LOCUS system [1]. It is shown how the traditional parity space outlier detection method overcomes robust methodologies when only one ranging error is present, whereas it is not able to detect two simultaneous faults. It is proposed a modification of the LTS robust estimation methodology that offers a good performance even when several range measurements are erroneous, due to multipath and occlusions effects. The complexity of the robust algorithms studied is low enough for being implemented in the 3D-LOCUS system without affecting its current 10 Hz update rate.

Indoor Localization of Persons in AAL Scenarios Using an Inertial Measurement Unit (IMU) and the Signal Strength (SS) from RFID Tags

This paper presents an indoor localization system that is based on the fusion of two complementary technologies: 1) Inertial integration and 2) RFID-based trilateration. The Inertial subsystem uses an IMU (Inertial Measurement Unit) mounted on the foot of the person. The IMU approach generates a very accurate estimate of the user’s trajectory shape (limited by the drift in yaw). However, being a dead-reckoning method, it requires an initialization in position and orientation to provide absolute positioning. The IMU-based solution is updated at 100 Hz and is always available. On the other hand, the RFID-based localization subsystem provides the absolute position using the Received Signal Strength (RSS) from several long-range active tags installed in the building. Since the transmitted RF signals are subject to many propagation artifacts (reflections, absorption,...), we use a probabilistic RSS-to-Range model and a Kalman filter to estimate the position. The output of both IMU- and RFID-based subsystems are fused into one final position estimation by adaptively fitting the IMU and RFID trajectories. The integrated solution provides: absolute positioning information, a static accuracy of less than 2.3 m (in 75% of the cases) for persons at fixed positions, a smooth trajectory for moving persons with a dynamic positioning accuracy of 1.1 m (75%), a full 100% availability, and a real-time update rate of up to 100 Hz. This approach is valid for indoor navigation and particularly for Ambient Assisted Living (AAL) applications. We presented this system to the 2nd EvAAL competition (“Evaluating AAL Systems through Competitive Benchmarking”: http://evaal.aaloa.org/ ) and our CAR-CSIC system was awarded with the first prize. A detailed analysis of the experiments during the competition is presented at the end of this paper.