Alpha-beta Filter Research Articles

Development of Web-Based Analysis System for Real-Time Decision Support on Arterial Networks

With increasing amounts of data being collected for intelligent transportation systems on arterial networks, the archival, management, and analysis of complex network traffic data have become a challenge. Challenges include inconsistent data connections, data quality control, query performance, traffic prediction, and computational limitations. The web-based RADAR Net system is presented to address these challenges. This system adopts a relational database with link, intersection, and detector entities. Relational data demonstrate its query performance and scalability. The system contains four layers: offline server, online server (middleware), online server (Java Servlet), and online client. This four-layer design successfully distributes the computational burden on the server. To monitor arterial performance, link speeds are calculated directly from loop detector data retrieved in Bellevue, Washington. The system can dynamically predict and smooth real-time loop spot speeds by using an alpha-beta filter (a simplified version of the Kalman filter) while maintaining high system performance. The link speeds of the entire network are calculated and updated in real time. Many application modules (e.g., for capacity analysis and dynamic routing) based on the system architecture have been implemented and have proven the system feasible for performing real-time analysis and assisting decision making.

A Combined Hard and Soft Variable-Structure Control Scheme for a Class of Nonlinear Systems

This paper presents a novel variable-structure-based control scheme for nonlinear systems. First, a hard variable-structure control is constructed for achieving a uniform ultimate boundedness control. Then, a soft variable-structure control using fuzzy logic is incorporated to help improve dynamic responses when trajectories enter into the ultimate bound. For practical consideration, we added a genetic-algorithm-based alpha-beta filter in front of the fuzzy controller to suppress noise and obtain smooth input signals. For comparison purposes, an inverted pendulum system was first used as a simulated example to demonstrate the effectiveness of the design. Then, the performance of the control scheme was practically tested with an experimental PC-based magnetic levitation system. The simulation and experimental results strongly suggest that the newly proposed control scheme is encouraging for practical applications.

A Practical Two-Input Single-Output Fuzzy Logic Controller with an Alpha-Beta Prefilter

This paper deals with the design of a practical two-input single-output (TISO) fuzzy logic controller for a nonlinear system. We firstly define two generalized errors for a nonlinear system and develop a stable feedback control scheme. Then a novel fuzzy logic controller is designed and incorporated into this scheme to achieve a better tracking response. The key feature of the proposed control scheme is that a discrete prefilter, called alpha-beta filter is placed in front of the fuzzy logic controller. The significance of using the Kalman-like fixed-gain filter is its capability of suppressing noise and feeding the fuzzy logic controller with smooth signals. From an implementation point of view, the discrete TISO fuzzy logic controller with the alpha-beta prefilter is believed to be quite simple, general and useful for practical applications. The validity of the proposed control scheme is verified through practical testing on the experimental setup called magnetic levitation system. The test results strongly suggest that the newly proposed control scheme is simple yet effective for use in a variety of feedback control systems.

Comparison of Four Filtering Options for a Radar Tracking Problem

Abstract : Four different filtering options are considered for the problem of tracking an exoatmospheric ballistic target with no maneuvers. The four filters are an alpha-beta filter, an augmented alpha-beta filter, a decoupled Kalman filter, and a fully-coupled extended Kalman filter. These filters are listed in the order of increasing computational complexity. All of the filters can track the target with some degree of accuracy. While the pure alpha-beta filter appreciably lags the other filters in performance for this problem, its augmented version is very competitive with the extended Kalman filter under benign conditions. Perhaps the most surprising result is that under all conditions examined, the decoupled (linear) Kalman filter, which is at least an order of magnitude less computationally complex, performs nearly identical to the coupled, extended Kalman filter. Four different filtering options are considered for the problem of tracking an exoatmospheric ballistic target with no maneuvers. The four filters are an alpha-beta filter, an augmented alpha-beta filter, a decoupled Kalman filter, and a fully-coupled extended Kalman filter. These filters are listed in the order of increasing computational complexity. All of the filters can track the target with some degree of accuracy. While the pure alpha-beta filter appreciably lags the other filters in performance for this problem, its augmented version is very competitive with the extended Kalman filter under benign conditions. Perhaps the most surprising result is that under all conditions examined, the decoupled (linear) Kalman filter, which is at least an order of magnitude less computationally complex, performs nearly identical to the coupled, extended Kalman filter.

A simple fixed-lag algorithm for tracking frequency rate-of-change

A family of simple fixed-lag frequency smoothing algorithms which provide good estimates of both frequency and frequency rate-of-change is reported. The smoothers were developed from a fixed-gain alpha beta tracker by replacing the recursive derivative estimator with a finite-impulse-response (FIR) differentiator. Simulation results are presented which show that the smoothing algorithms provide frequency estimates with a similar variance to those produced by the alpha beta filter but with greatly improved frequency-rate estimates. The smoothing algorithms and the alpha beta filter are also compared on the basis of the bias and delay introduced in the frequency-rate estimates. Although the results presented are for frequency estimation, the smoothing algorithms can be used in any single-input tracking application where some lag in the estimates is allowable.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The alpha-beta filter

The alpha-beta filter

Reconciling steady-state Kalman and alpha-beta filter design

The deterministic design of the alpha-beta filter and the stochastic design of its Kalman counterpart are placed on a common basis. The first step is to find the continuous-time filter architecture which transforms into the alpha-beta discrete filter via the method of impulse invariance. This yields relations between filter bandwidth and damping ratio and the coefficients, alpha and beta . In the Kalman case, these same coefficients are related to a defined stochastic signal-to-noise ratio and to a defined normalized tracking error variance. These latter relations are obtained from a closed-form, unique, positive-definite solution to the matrix Riccati equation for the tracking error covariance. A nomograph is given that relates the stochastic and deterministic designs. >

Adaptive variable update rate algorithm for tracking targets with a phased array radar

The analysis postulates an algorithm for adaptively varying the target-track update rate as a function of target manoeuvring. The algorithm proposes to vary the target observation time interval by an amount that tends to maintain a constant residual error. As an example, the algorithm is shown to be implemented with a two-dimensional alpha-beta filter. Simulated results are calculated for a target manoeuvre consisting of a single 90° turn. The results show that when a manoeuvre is detected, the sampling time interval can be reduced rapidly to facilitate tracking with reduceed error. After the manoeuvre, the sampling interval is increased automatically so more time can be made available to the phased array radar for other activities.