A Basic Study on Development of a Tracking Module for ARPA system for Use on High Dynamic Warships

Anne Wanjiru Njonjo,Bao-Feng Pan,Tae-Gweon Jeong 한국항해항만학회 2016 한국항해항만학회지 Vol.40 No.2

The maritime industry is expanding at an alarming rate hence there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking module designed herein comprises determining existing states of high dynamic target warship, state prediction and state compensation due to random noise. This is achieved by first analyzing the process of tracking followed by design of a tracking algorithm that uses α-β-γ tracking filter under a random noise. The algorithm involves initializing the state parameters which include position, velocity, acceleration and the course. This is then followed by state prediction at each time interval. A weighted difference of the observed and predicted state values at the nth observation is added to the predicted state to obtain the smoothed (filtered) state. This estimation is subsequently employed to determine the predicted state in the next radar scan. The filtering coefficients ,  and  are determined from a pre- determined value of the damping parameter, . The smoothed, predicted and the observed positions are used to compute the twice distance root mean square (2drms) error as a measure of the ability of the tracking module to manage the noise to acceptable levels.

Basic Study of a Comparison of the Performances of the α-β-γ Filter and the Kalman Filter Regarding Their Use in the ARPA-System Tracking Module of High-Dynamic Warships

Njonjo, Anne Wanjiru,Pan, Bao-Feng,Jeong, Tae-Gweon Korean Institute of Navigation and Port Research 2017 한국항해항만학회지 Vol.41 No.5

"Tracking" here refers to the estimation of a moving object with some degree of accuracy where at least one measurement is given. The measurement, which is the sensor-obtained output, contains systemic errors and errors that are due to the surrounding environment. Tracking filters play the key role of the target-state estimation after the updating of the tracking system; therefore, the type of filter that is used for the conduction of the estimations is crucial in the determining of the reliability of the updated value, and this is especially true since the performances of different filters vary when they are subjected to different environmental and initial conditions. The purpose of this paper is the conduction of a comparison between the performances of the ${\alpha}-{\beta}-{\gamma}$ filter and the Kalman filter regarding an ARPA-system tracking module that is used on board high-dynamic warships. The comparison is based on the capability of each filter to reduce noise and maintain a stable response. The residual error is computed from the difference between the true and predicted positions and the true and estimated positions for the given sample. The results indicate that the tracking accuracy of the Kalman filter is higher compared with that of the optimal ${\alpha}-{\beta}-{\gamma}$ filter; however, the response of the optimal ${\alpha}-{\beta}-{\gamma}$ filter is more stable.

Basic Study of a Comparison of the Performances of the α-β-γ Filter and the Kalman Filter Regarding Their Use in the ARPA-System Tracking Module of High-Dynamic Warships

Anne Wanjiru Njonjo,Bao-Feng Pan,Tae-Gweon Jeong 한국항해항만학회 2017 한국항해항만학회지 Vol.41 No.5

“Tracking” here refers to the estimation of a moving object with some degree of accuracy where at least one measurement is given. The measurement, which is the sensor-obtained output, contains systemic errors and errors that are due to the surrounding environment. Tracking filters play the key role of the target-state estimation after the updating of the tracking system; therefore, the type of filter that is used for the conduction of the estimations is crucial in the determining of the reliability of the updated value, and this is especially true since the performances of different filters vary when they are subjected to different environmental and initial conditions. The purpose of this paper is the conduction of a comparison between the performances of the α-β-γ filter and the Kalman filter regarding an ARPA-system tracking module that is used on board high-dynamic warships. The comparison is based on the capability of each filter to reduce noise and maintain a stable response. The residual error is computed from the difference between the true and predicted positions and the true and estimated positions for the given sample. The results indicate that the tracking accuracy of the Kalman filter is higher compared with that of the optimal α-β-γ filter; however, the response of the optimal α-β-γ filter is more stable.

A Basic Study on Development of a Tracking Module for ARPA system for Use on High Dynamic Warships

Anne Wanjiru Njonjo,Bao Feng Pan,Tae Gweon Jeong 한국항해항만학회 2016 한국항해항만학회지 Vol.40 No.2

The maritime industry is expanding at an alarming rate hence there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking module designed herein comprises determining existing states of high dynamic target warship, state prediction and state compensation due to random noise. This is achieved by first analyzing the process of tracking followed by design of a tracking algorithm that uses α-β-γ tracking filter under a random noise. The algorithm involves initializing the state parameters which include position, velocity, acceleration and the course. This is then followed by state prediction at each time interval. A weighted difference of the observed and predicted state values at the nth observation is added to the predicted state to obtain the smoothed (filtered) state. This estimation is subsequently employed to determine the predicted state in the next radar scan. The filtering coefficients α, β, and γ are determined from a pre- determined value of the damping parameter, ξ. The smoothed, predicted and the observed positions are used to compute the twice distance root mean square (2drms) error as a measure of the ability of the tracking module to manage the noise to acceptable levels.

A Study of Optimization of α-β-γ-η Filter for Tracking a High Dynamic Target

Pan, Bao-Feng,Njonjo, Anne Wanjiru,Jeong, Tae-Gweon Korean Institute of Navigation and Port Research 2017 한국항해항만학회지 Vol.41 No.5

The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel's position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity ${\alpha}-{\beta}$ filter, the ${\alpha}-{\beta}-{\gamma}$ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The ${\alpha}-{\beta}-{\gamma}$ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter's performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, ${\alpha}-{\beta}-{\gamma}-{\eta}$ algorithm as compared to the constant acceleration model, ${\alpha}-{\beta}-{\gamma}$ in terms of error reduction and stability of the filter during target maneuver.

A Study of Optimization of α - β - γ - η Filter for Tracking a High Dynamic Target

Bao-Feng Pan,Anne Wanjiru Njonjo,Tae-Gweon Jeong 한국항해항만학회 2017 한국항해항만학회지 Vol.41 No.5

The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel’s position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The α- β - γ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity α - β filter, the α - β - γ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The α - β - γ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter’s performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, α - β - γ - η algorithm as compared to the constant acceleration model, α - β - γ in terms of error reduction and stability of the filter during target maneuver.

Optimization of the Gain Parameters in a Tracking Module for ARPA system on Board High Dynamic Warships

Bao-Feng Pan,Anne Wanjiru Njonjo,Tae-Gweon Jeong 한국항해항만학회 2016 한국항해항만학회지 Vol.40 No.5

The tracking filter plays a key role in the accurate estimation and prediction of maneuvering a vessel’s position and velocity when attempting to enhance safety by avoiding collision. Therefore, in order to achieve accurate estimation and prediction, many oceangoing vessels are equipped with the Automatic Radar Plotting Aid (ARPA) system. However, the accuracy of prediction depends on the tracking filter’s ability to reduce noise and maintain a stable transient response. The purpose of this paper is to derive the optimal values of the gain parameters used in tracking a High Dynamic Warship. The algorithm employs a filter to provide accurate estimates and updates of the state variables, that is, positions, velocity and acceleration of the high dynamic warship based on previously observed values. In this study, the filtering coefficients and are determined from set values of the damping parameter. Optimization of the damping parameter , is achieved experimentally by plotting the residual error against different values of the damping parameter to determine the least value of the damping parameter that results in the optimum smoothing coefficients leading to a reduction in the noise corruption effect. Further investigation of the performance of the filter indicates that optimal smoothing coefficients depend on the initial and average velocity of the target.

Theoretical Approach of Optimization of the Gain Parameters α, β and γ of a Tracking Module for ARPA system on Board Warships

Tae-Gweon Jeong,Bao-Feng Pan,Anne Wanjiru Njonjo 한국항해항만학회 2015 한국항해항만학회 학술대회논문집 Vol.2015 No.추계

The tracking system plays a key role in accurate estimation and prediction of maneuvering vessel’s position and velocity in a bid to enhance safety by taking avoiding action against collision. Therefore, in order to achieve this, many ocean- going vessels are equipped with radar and the ARPA system. However, the accuracy of prediction highly depends on the choice of the gain parameters, α, β and γ employed in the tracking filter. Previous research of this paper was based on theoretically developing an algorithm for a tracking module. This research paper is hence a continuation by the authors to determine the optimal values of the gain parameters used in the tracking module. A tracking algorithm is developed using the α- β- γ filter to carry out prediction and smoothing of the positions and velocities. Numerical simulations are then performed to evaluate the optimal values of the smoothing parameters that will improve the performance of the tracking module and reduce measurement noise. The twice distance root mean square (2drms) is then calculated to determine error variation.

Theoretical Approach of Development of Tracking Module for ARPA system on Board Warships

Tae-Gweon Jeong,Bao-Feng Pan,Anne Wanjiru Njonjo 한국항해항만학회 2015 한국항해항만학회 학술대회논문집 Vol.2015 No.추계

The maritime industry is expanding at an alarming rate and as such there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking system described herein comprises determining existing states of own ship, state prediction and state compensation caused by random noise. The purpose of this paper is to analyze the process of tracking and develop a tracking algorithm by using α-β-γ tracking filter under a random noise or irregular motion for use in a warship. The algorithm involves initializing the input parameters of position, velocity and course. The actual positions are then computed for each time interval. In addition, a weighted difference of the observed and predicted position at the nth observation is added to the predicted position to obtain the smoothed position. This estimation is subsequently employed to determine the predicted position at (n+1). The smoothed values, predicted values and the observed values are used to compute the twice distance root mean square (2drms) error as a measure of accuracy of the tracking module.