Hyeonwoo Cho

Mobile Robot Localization Using Biased Chirp-Spread-Spectrum Ranging

In this paper, we propose a method of mobile robot localization based on chirp-spread-spectrum (CSS) ranging. By using the CSS system, the distances between a mobile robot and CSS nodes fixed at known coordinates can be measured according to the time of flight of radio frequency signals. Based on the measured distances, the coordinates of a mobile robot can be calculated by the method of trilateration. To deal with measurement noise, an extended Kalman filter (EKF) can be applied to estimate the coordinate of the mobile robot. These measured distances, however, are not only noisy but also biased. Therefore, the estimated coordinates of the mobile robot represent inconsistent values. To solve the problem of bias, we define a scaling factor, which corresponds to the change of the magnitude of a measured distance vector that is due to biases. Based on the scaling factor, we develop a new biased measurement model and apply the EKF to our model for estimating the coordinates of a mobile robot. Through localization experiments, we evaluate the performance of the proposed algorithm.

Fast communication: Derivation of a new normalized least mean squares algorithm with modified minimization criterion

In this letter, we propose a normalized least mean squares (NLMS) algorithm with a new minimization criterion that minimizes the summation of each squared Euclidean norm of difference between the currently updated coefficient vector and past coefficient vectors. Through simulations, we show that the proposed NLMS algorithm has lower misalignment than the conventional NLMS algorithm.

An Adaptive RFID Anti-Collision Algorithm Based on Dynamic Framed ALOHA

The collision of ID signals from a large number of colocated passive RFID tags is a serious problem; to realize a practical RFID systems we need an effective anti-collision algorithm. This letter presents an adaptive algorithm to minimize the total time slots and the number of rounds required for identifying the tags within the RFID readers interrogation zone. The proposed algorithm is based on the framed ALOHA protocol, and the frame size is adaptively updated each round. Simulation results show that our proposed algorithm is more efficient than the conventional algorithms based on the framed ALOHA.

An enhanced positioning scheme for chirp spread spectrum ranging

In this paper, we propose an algorithm for acquiring enhanced position coordinates when using the chirp spread spectrum (CSS) specified in IEEE 802.15.4a. Because the measured distances are generally perturbed by measurement noise, the extended Kalman filter (EKF) can be applied to trilateration to treat the variation in the measured distances due to the noise. In practice, the average value of many measured distances obtained using the CSS is not equal to the true distance, because the noise in the measurement has a nonzero mean; that is, a nonzero average error exists. Because the EKF is only suitable for a case with zero mean noise, the average error needs to be eliminated in advance. For this purpose, we propose a minimization criterion that determines weighting parameters. The average error is reduced by multiplying measured distances by the weighting parameters. To verify the performance of the proposed method, we conduct experiments for the CSS-based positioning of given targets, and compare the results for the EKF with and without the proposed algorithm. From the results, we can find that the coordinates estimated by the EKF with the proposed algorithm are more accurate.

Fast communication: Variable step-size normalized LMS algorithm by approximating correlation matrix of estimation error

In this letter, we propose a variable step-size normalized least mean square (NLMS) algorithm. We study the relationship among the NLMS, recursive least square and Kalman filter algorithms. Based on the relationship, we derive an equation to determine the step-size of NLMS algorithm at each time instant. In steady state, the convergence of the proposed algorithm is verified by using the equation, which describes the relationship among the mean-square error, excess mean-square error, and measurement noise variance. Through computer simulation results, we verify the performance of the proposed algorithm and the change in the variable step-size over iterations.

Fast communication: A variable step-size adaptive algorithm for direct frequency estimation

A frequency estimator based on the linear prediction property of sinusoidal signals has recently been proposed for the direct estimation of real tone frequency in white noise. We propose a variable step-size direct frequency estimator (VS-DFE), which shows improved performance on account of the use of a dynamically updated step-size instead of a fixed step-size. A comparison of the simulation results of the proposed estimator with those of conventional estimators clearly indicates its superior performance.

Localization for a Mobile Node Based on Chrip Spread Spectrum Ranging

In this paper, we propose a localization algorithm for a mobile node based on the IEEE 802.15.4a chirp spread spectrum (CSS). IEEE 802.15.4a is an alternative PHY for IEEE 802.15.4, which is used for wireless sensor networks, and it can be applied to ranging applications. Through CSS ranging, the coordinate of a CSS node can be calculated by using trilateration. This approach is usually used for mobile robot localization. In the case of mobile robot localization, the dynamics of a mobile robot can be modeled as a state-space equation because a robot is an artificial object manufactured by designers. Therefore, the coordinate of a mobile robot can be estimated by using the Kalman filter. However, in the case of localization of a mobile node whose movement cannot be predicted, the dynamics of the mobile node are difficult to model. Therefore, we propose a strategy that regards the un-modeled dynamics as the process noise of the state-space equation. Further, we propose a method for determining the statics of the process noise based on some reasonable assumptions. Through the localization experiment, we verify the proposed method and discuss the results.

Observability-Based Selection Criterion for Anchor Nodes in Multiple-Cell Localization

The coverage of localization systems for a mobile robot can be expanded by using a multiple-cell structure. In such a structure, there are a number of anchor nodes installed at several positions whose coordinates are known in advance. Therefore, the mobile robot must select some anchor nodes that are suitable for its localization. As a selection criterion for these anchor nodes, the strength of the received ranging signal has been used in the conventional manner, but this approach is highly dependent on the particular environment. In this paper, we focus on the recently proposed localization model for biased chirp spread spectrum ranging. To apply the model to multiple-cell localization, we propose a selection criterion for anchor nodes that is based upon the observability of the model. The proposed criterion assures that the estimated coordinates by the extended Kalman filter can track the actual position of the mobile robot when it is located at the boundary of two adjacent cells.

Development of passive acoustic landmark using imaging sonar for AUV's localization

We proposed and tested a passive acoustic landmark that can provide accurate navigation information for an autonomous underwater vehicle (AUV). The AUV used imaging sonar mounted on the vehicle to recognize shadows of the columntype landmark, and can measure vehicles own pose and relative position from the landmark which was set in a known position. The results of the proposed method had acceptable error (<;1 %) in the calculated position of the AUV. The proposed localization method will be useful to correct drift errors of inertial navigation systems for the AUV or to find the same position repeatedly.

Derivation of Excess Mean-Square Error for Affine Projection Algorithms Using the Condition Number

This paper presents a numerical expression for the excess mean-square error (EMSE) of affine projection(AP) algorithms, and the expression is proportional to the data reuse factor and the condition number of the input data. For the condition number, a recently reported technique developed by using E-norm is adopted instead of L2-norm. The proposed expression offers an insight into the mechanics of the AP algorithm by including the condition number in the EMSE. Our simulation results show a relatively good match between the proposed expression and the practice.