James Calusdian

Estimation of Human Foot Motion During Normal Walking Using Inertial and Magnetic Sensor Measurements

A foot motion filtering algorithm is presented for estimating foot kinematics relative to an earth-fixed reference frame during normal walking motion. Algorithm input data are obtained from a foot-mounted inertial/magnetic measurement unit. The sensor unit contains a three-axis accelerometer, a three-axis angular rate sensor, and a three-axis magnetometer. The algorithm outputs are the foot kinematic parameters, which include foot orientation, position, velocity, acceleration, and gait phase. The foot motion filtering algorithm incorporates novel methods for orientation estimation, gait detection, and position estimation. Accurate foot orientation estimates are obtained during both static and dynamic motion using an adaptive-gain complementary filter. Reliable gait detection is accomplished using a simple finite state machine that transitions between states based on angular rate measurements. Accurate position estimates are obtained by integrating acceleration data, which has been corrected for drift using zero velocity updates. Algorithm performance is examined using both simulations and real-world experiments. The simulations include a simple but effective model of the human gait cycle. The simulation and experimental results indicate that a position estimation error of less than 1% of the total distance traveled is achievable using commonly available commercial sensor modules.

Adaptive-gain complementary filter of inertial and magnetic data for orientation estimation

Accurate estimation of orientation based on data from small low-cost strapdown inertial and magnetic sensors is often inaccurate during highly dynamic motion or when trying to track movements that include two or more periods characterized by significantly different frequencies. This paper presents a complementary filtering algorithm for estimating orientation based on inertial/magnetic sensor measurements. The algorithm takes advantage of the complementary nature of the information offered by high-frequency angular rate sensor data and low-frequency accelerometers and magnetometers. The filtering algorithm utilizes a single gain that can be adaptively adjusted to achieve satisfactory performance while tracking two or more different types of motion. An additional feature of our approach involves the simple estimation of the gyro bias during periods exhibiting low dynamics and its subsequent use to correct the instantaneous gyro measurements. Simulation and experimental results are presented that demonstrate the performance of the algorithm during slow or nearly static movements, as well as, those which are highly dynamic. Experimental results indicate that the algorithm is able to track pitch and roll during dynamic motion with an RMS error of less than two degrees. This is believed to be superior to current proprietary commercial algorithms.

Going anywhere anywhere: Creating a low cost portable immersive VE system

In general, the use of VE (Virtual Environment) systems has required users to travel to specialized facilities in which an expensive infrastructure has been pre-installed. Often these facilities allow only one user at a time, and users usually move through virtual worlds by means of an artificial interface device or a movement metaphor. In short, most VR facilities are centralized, specialized, and expensive, and have thus been relatively unavailable to a great majority of the population. This paper reports on the development of an innovative immersive VE system that is completely portable. The proposed system would allow multiple users to be immersed simultaneously and could be used in any large indoor or outdoor area such as a gymnasium or parking lot. Users will move through virtual worlds naturally, and will be able to walk for miles in a virtual world without ever becoming aware of the physical limits of the tracking space or the locations of other users. The portable system will cost far less than current systems. The research hinges on three emerging techniques. The first is redirected walking (RDW). The second is self-contained inertial position tracking (SCIPT). The last is the use of ultrasonic and/or laser ranging systems to simultaneously localize and map (SLAM) within an unfamiliar tracking area. The paper describes the effort that is underway and reports preliminary results which have been obtained in each of these areas over the last few years.

Robust symmetrical number system preprocessing for minimizing encoding errors in photonic analog-to-digital converters

A photonic analog-to-digital converter (ADC) preprocessing architecture based on the robust symmetrical number system (RSNS) is presented. The RSNS preprocessing architecture is a modular scheme in which a modulus number of comparators are used at the output of each Mach-Zehnder modulator channel. The number of comparators with a logic 1 in each channel represents the integer values within each RSNS modulus sequence. When considered together, the integers within each sequence change one at a time at the next code position, resulting in an integer Gray code property. The RSNS ADC has the feature that the maximum nonlinearity is less than a least significant bit (LSB). Although the observed dynamic range (greatest length of combined sequences that contain no ambiguities) of the RSNS ADC is less than the optimum symmetrical number system ADC, the integer Gray code properties make it attractive for error control. A prototype is presented to demonstrate the feasibility of the concept and to show the important RSNS property that the largest nonlinearity is always less than a LSB. Also discussed are practical considerations related to multi-gigahertz implementations.

In situ heading drift correction for human position tracking using foot-mounted inertial/magnetic sensors

This paper presents a heading drift correction method and experimental results for position tracking of human movement based on the use of foot-mounted inertial/magnetic sensor modules. A position tracking algorithm was previously developed, which incorporated a zero velocity update technique for correcting accelerometer drift. Previous experiments indicated the presence of a persistent heading drift in the estimated position. In this paper, a simple method for correcting this drift is presented. The method requires the user to walk over a closed loop path with the foot-mounted sensor module. Assuming a constant sensor bias for this initial walk, the resulting position error is then used to accomplish an in situ correction for position estimates during future walks. Experimental results validate the effectiveness of the drift correction method and show a significant improvement in position tracking accuracy. Accuracy is determined based on the final position estimates following walks of 100 and 400 meters. Estimated distance traveled averages within 0.2% of actual distance traveled and distance from the actual position averages within 0.28% of actual distance traveled.

Wideband direction finding using a photonic robust symmetrical number system technique

Abstract. Dual electrode Mach–Zehnder modulators (DE-MZMs) are used to conduct phase detection for direct wideband direction finding (DF) of microwave signals. It is demonstrated theoretically and through simulation and experimentation that the normalized magnitude of the output signal phase detector circuit is equal to |sin(ψ/2)|, where ψ is the phase difference between the plane waves arriving at the reference and measurement antennas of a linear DF array. A four-element wideband photonic DF system with robust symmetrical number system preprocessing is presented. Simulation and experimental testing results are provided to demonstrate the theoretical concept. The results demonstrate a direct DF receiver using DE-MZMs that achieves fine angular resolution using a much smaller array size than is typically required for linear arrays employing super-resolution signal processing techniques.

Testing and evaluation of an inertial/magnetic sensor-based pen input device

Testing and evaluation of a novel pen input device are presented in this paper. The pen input device could be used to write on any type of surface including desktops, blackboards, or in the air. It is constructed by attaching an inertial/magnetic sensor module to a writing instrument such as a pencil, a marker, or a piece of chalk. The inertial/magnetic sensor module has three accelerometers, three angular rate sensors, and three magnetometers. A tracking algorithm and a calibration algorithm are described. The tracking algorithm is for estimating the pen tip trajectories based on the sensor measurements, and the calibration algorithm is for estimating the relative position of the sensor module on the writing instrument. Experimental results for writing alphanumeric characters are presented. The relationship between tracking accuracy and writing speed is also discussed.

Encoding Scheme Minimizes Errors in Photonic Converters

Abstract : Digitizing wideband radio frequency (RF) signals directly at the antenna is important in defense systems such as electronic warfare digital receivers and electronic signal intelligence collectors. It can eliminate the need for down-conversion to intermediate frequencies that cause spurious signals at the output of the receiver s analog-to-digital converter (ADC). Digitization also can hide any low power signals of interest. A new scheme with an inherent integer Gray code property reduces photonic analog-to-digital converter errors while enhancing resolution.