A performance improvement method for low-cost land vehicle GPS/MEMS-INS attitude determination.

Global positioning system (GPS) technology is well suited for attitude determination. However, in land vehicle application, low-cost single frequency GPS receivers which have low measurement quality are often used, and external factors such as multipath and low satellite visibility in the densely built-up urban environment further degrade the quality of the GPS measurements. Due to the low-quality receivers used and the challenging urban environment, the success rate of the single epoch ambiguity resolution for dynamic attitude determination is usually quite low. In this paper, a micro-electro-mechanical system (MEMS)-inertial navigation system (INS)-aided ambiguity resolution method is proposed to improve the GPS attitude determination performance, which is particularly suitable for land vehicle attitude determination. First, the INS calculated baseline vector is augmented with the GPS carrier phase and code measurements. This improves the ambiguity dilution of precision (ADOP), resulting in better quality of the unconstrained float solution. Second, the undesirable float solutions caused by large measurement errors are further filtered and replaced using the INS-aided ambiguity function method (AFM). The fixed solutions are then obtained by the constrained least squares ambiguity decorrelation (CLAMBDA) algorithm. Finally, the GPS/MEMS-INS integration is realized by the use of a Kalman filter. Theoretical analysis of the ADOP is given and experimental results demonstrate that our proposed method can significantly improve the quality of the float ambiguity solution, leading to high success rate and better accuracy of attitude determination.

Generalized eigenvalue minimization for uncertain first-order plus time-delay processes.

This paper shows how to apply generalized eigenvalue minimization to processes that can be described by a first-order plus time-delay model with uncertain gain, time constant and delay. An algorithm to transform the uncertain first-order plus time delay model into a state-space model with uncertainty polyhedron is firstly described. The accuracy of the transformation is studied using numerical examples. Then, the uncertainty polyhedron is rewritten as a linear-matrix-inequality constraint and generalized eigenvalue minimization is adopted to calculate a feedback control law. Case studies show that even if uncertainties associated with the first-order plus time delay model are significant, a stable feedback control law can be found. The proposed control is tested by comparing with a robust internal model control. It is also tested by applying it to the temperature control of air-handing units.

Evaluation on similarity measures of a surface-to-image registration technique for ultrasound images.

Ultrasound is a universal guidance tool for many medical procedures, whereas it is of poor image quality and resolution. Merging high-contrast image information from other image modalities enhances the guidance capability of ultrasound. However, few registration methods work well for it. In this paper we present a surface-to-image registration technique for mono- or multimodal medical data concerning ultrasound. This approach is able to automatically register the object surface to its counterpart in image volume. Three similarity measurements are investigated in the rigid registration experiments of the pubic arch in transrectal ultrasound images. It shown that the selection of the similarity function is related to the ultrasound characteristics of the object to be registered.

Online parameter estimation for surgical needle steering model.

Estimation of the system parameters, given noisy input/output data, is a major field in control and signal processing. Many different estimation methods have been proposed in recent years. Among various methods, Extended Kalman Filtering (EKF) is very useful for estimating the parameters of a nonlinear and time-varying system. Moreover, it can remove the effects of noises to achieve significantly improved results. Our task here is to estimate the coefficients in a spring-beam-damper needle steering model. This kind of spring-damper model has been adopted by many researchers in studying the tissue deformation. One difficulty in using such model is to estimate the spring and damper coefficients. Here, we proposed an online parameter estimator using EKF to solve this problem. The detailed design is presented in this paper. Computer simulations and physical experiments have revealed that the simulator can estimate the parameters accurately with fast convergent speed and improve the model efficacy.

Class of 4 + 1-phase algorithms with error compensation.

It is well known that phase-shifting interferometry suffers from inaccuracy in the presence of phase-shifting errors. We have proved the limitation of using a 4-phase algorithm to reduce the phase-measurement error in the presence of the phase-shifting error. A class of 4 + 1-phase error compensating algorithms is formulated. It is shown that the proposed algorithms can effectively minimize the effects of the constant phase-shifting error and possess a superior performance than existing error-compensating algorithms. The effectiveness of the proposed algorithm is demonstrated by computer simulations and experiments.

Prostate boundary detection from ultrasonographic images.

OBJECTIVE: Prostate diseases are very common in adult and elderly men, and prostate boundary detection from ultrasonographic images plays a key role in prostate disease diagnosis and treatment. However, because of the poor quality of ultrasonographic images, prostate boundary detection still remains a challenging task. Currently, this task is performed manually, which is arduous and heavily user dependent. To improve the efficiency by automating the boundary detection process, numerous methods have been proposed. We present a review of these methods, aiming to find a good solution that could efficiently detect the prostate boundary on ultrasonographic images. METHODS: A full description of various methods is beyond the scope of this article; instead, we focus on providing an introduction to the different methods with a discussion of their advantages and disadvantages. Moreover, verification methods for estimating the accuracies of the algorithms reported in the literature are discussed as well. RESULTS: From the investigation, we summarize several key issues that might be confronted and project possible future research. CONCLUSIONS: Those model-based methods that minimize user involvement but allow for interactive guidance of experts will likely be most immediately successful.