A gyroscope-free inertial navigation system uses only accelerometers to compute navigation trajectories. It is a low-cost navigation system, but its output error diverges at a rate that is an order faster than that of a conventional gyroscope-based system. So integration with an external reference system, such as the Global Positioning System, is necessary for long-term navigation applications. In this pa-per, an integrated GPS and gyroscope-free INS system is designed to achieve stable long-term navigation. The linear and nonlinear error models of a gyroscope-free INS are derived and are used as Kalman filter equations to estimate the errors in the gyroscope-free INS data. The effects of gyroscope-free inertial measurement unit errors are also analyzed. By using computer simulations, the performance of the integrated GPS and gyroscope-free INS system is verified.

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University of California Institute of Transportation Studies (9) Institute of Transportation Studies at UC Berkeley (9) California Partners for Advanced Transportation Technology (9)

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## Scholarly Works (21 results)

We examine the feasibility of designing an accelerometer-based (or gyroscope-free) inertial navigation system that uses only accelerome-ters to compute the linear and angular motions of a rigid body. The accelerometer output equation is derived to relate the linear and an-gular motions of a rigid body relative to a fixed inertial frame. A suf-ficient condition is given to determine if a configuration of accelerom-eters is feasible. If the condition is satisfied, the angular and linear motions can be computed separately using two decoupled equations of an input-output dynamical system; a state equation for angular velocity and an output equation for linear acceleration. This simple computation scheme is derived from the corresponding dynamical sys-tem equations for a special cube configuration for which the angular acceleration is expressed as a linear combination of the accelerometer outputs. The effects of accelerometer location and orientation errors are analysed. Algorithms that identify and compensate these errors are developed. Keywords gyroscope-free, configuration of accelerometers, feasibility, input-output dynamical system realisation, error sensitivity analysis.

This report presents adaptive control algorithms for conventional modes of operation of MEMS z-axis gyroscopes. In an open-loop mode, an off-line self-calibration scheme is proposed for estimating fabrication imperfections and enhancing the performance of a gyroscope operating in open-loop mode. This scheme can be implemented during the initial calibration stage when the gyroscope is turned on, or at regular calibration sessions, which may be performed periodically. An adaptive add-on control scheme is also proposed for a closed-loop mode of operation. This scheme is realized by adding an outer loop to a conventional force-balancing scheme that includes a parameter estimation algorithm. This parameter adaptation algorithm estimates the angular rate, identifies and compensates the quadrature error, and may permit on-line automatic mode tuning. The convergence and resolution analysis show that the proposed adaptive add-on control scheme prevents the angular rate estimate from being contaminated by the quadrature error, while keeping ideal resolution performance of a conventional force-balancing scheme.

The current lane change maneuver for vehicles in a platoon under the California PATH automated highway system (AHS) architecture is inefficient, because the follower has to split from the rest of the platoon before making a lane change. In this report, we propose to add a lane change within platoons maneuver that allows a follower to change lanes and be inserted into another platoon directly without splitting either platoon. This maneuver is performed by aligning and locking the longitudinal positions of the two platoons in adjacent lanes. The estimated improvement in the AHS utilization, in term of the space-time, is approximately 4342 ms. The longitudinal controller for the lane changing follower is designed and proved to maintain the string stability of the platoons. The leader law is modified for the common leader of the two locked platoons. An intra-platoon spacing adjustment procedure is also designed for the purpose of the proposed maneuver.

This report presents a new adaptive operation strategy for MEMS z-axis gyroscopes. Specifically, a unified methodology is proposed for designing and analyzing the performance of a control algorithm that can identify and, in an adaptive fashion, compensate for most fabrication defects and perturbations affecting the behavior of a MEMS z-axis gyroscope. Dynamic analysis of typical MEMS gyroscopes shows that fabrication imperfections are a major factor limiting the performance of the gyroscope. However, the motion of a conventional mode-matched z-axis gyroscope does not have sufficient persistence of excitation and, as a result, all major fabrication imperfections cannot be identified and compensated for in an on-line fashion. The proposed adaptive control algorithm with velocity estimation, which operates with only measurements of the x and y positions of the proof mass, estimates the component of the angular velocity vector, which is orthogonal to the plane of oscillation of the gyroscope (the z-axis) and the linear damping and stiffness model coefficients in an on-line fashion. The convergence and resolution analysis presented in report showed that the proposed adaptive controlled scheme offers several advantages over conventional modes of operation. These advantages include a larger operational bandwidth, absence of zero-rate output, self-calibration and a large robustness to parameter variations, which are caused by fabrication defects and ambient conditions.

We study the feasibility of designing an accelerometer-based gyroscope-free inertial navigation system (INS) that uses only accelerometers to compute the linear and angular motions of a rigid body.

In this report, we present a hybrid discrete/ continuous time version of the observer-based adaptive control system for MEMS gyroscopes developed in [8], which can be readily implemented using digital processors. The control algorithm considered in this report is not fully a discrete time controller, since only the feedback control, parameter adaptation algorithms and feedforward control law are implemented in discrete time, while the velocity observer is still implemented in continuous time. A stochastic analysis of this algorithm is developed and it shows that the estimates of the angular rate and the fabrication imperfections are biased due to the signal discretization errors in the feedforward control path introduced by the sampler and holder. Thus, a two-rate discrete time control is proposed as a compromise between the measurement biases due to discretization errors and the computational burden imposed on the controller due to a fast sampling rate. The convergence analysis of this algorithm is also conducted and an analysis method is developed for determining the trade-off between the controller sampling frequency and the magnitude of the angular rate estimate biased errors. All convergence and stochastic properties of a continuous time adaptive control are preserved, and this analysis is verified with computer simulations.

This report presents the algorithm development and experimental work of the sensor node signal processing for vehicle detection. The signals used for vehicle detection are acoustic and magnetic signals. The acoustic signals are characterized by short time FFT analysis and two acoustic vehicle detection algorithms are proposed: the Adaptive Threshold algorithm (ATA) and the Min-max algorithm (MMA). The ATA detects vehicle by searching for a sequence of 1's after slicing the acoustic energy curve using an adaptive threshold. The MMA detects vehicles by searching the local maximum in the acoustic energy curve. Real time tests and offline simulations demonstrate the effectiveness of the two algorithms. For magnetic signals, a simple threshold slicing algorithm is utilized and real time tests give good performance. Finally, FPGA implementation of ATA is also presented for power efficiency requirement and the implementation justifies the use of dedicated hardware for low power implementation.

Wireless magnetic sensor networks offer a very attractive, low-cost alternative to inductive loops for traffic measurement in freeways and at intersections. In addition to vehicle count, occupancy and speed, the sensors yield traffic information (such as vehicle classification) that cannot be obtained from loop data. Because such networks can be deployed in a very short time, they can also be used (and reused) for temporary traffic measurement. This paper reports the detection capabilities of magnetic sensors, based on two field experiments. The first experiment collected a two-hour trace of measurements on Hearst Avenue in Berkeley. The vehicle detection rate is better than 99 percent (100 percent for vehicles other than motorcycles); and estimates of vehicle length and speed appear to be better than 90 percent. Moreover, the measurements also give inter-vehicle spacing or headways, which reveal such interesting phenomena as platoon formation downstream of a traffic signal. Results of the second experiment are preliminary. Sensor data from 37 passing vehicles at the same site are processed and classified into 6 types. Sixty percent of the vehicles are classified correctly, when length is not used as a feature. The classification algorithm can be implemented in real time by the sensor node itself, in contrast to other methods based on high scan-rate inductive loop signals, which require extensive offline computation. We believe that when length is used as a feature, 80-90 percent of vehicles will be correctly classified.