Self-aligned position estimation for low-power GPS receivers

The positioning services provided by the Global Positioning System (GPS) have been deployed in numerous portable/handheld applications. The major requirements of these devices are light weight, small size and long period between battery recharges. With the advance of integrated circuit technology, the major factor influencing the device weight and size becomes the amount of batteries required. However, compared to the "doubling speed" for integrated circuit technology, the time scale for battery improvement is relative long. Therefore achieving low power consumption to reduce the amount of energy required becomes necessary for these applications. Many methods exist for low power design. They range from optimizing at technology level, circuit level to architecture level. In this work, a system level optimization is performed to further lower power consumption.; The proposed self-regulated low-power (SRLP) algorithm uses a behavior model to describe the user's moving pattern. A Kalman filter without external aids, called an autonomous Kalman filter, is implemented to extract user's moving behavior and to smooth the position measurements from a GPS receiver. By comparing the outputs from the autonomous Kalman filter and that from the GPS receiver, a pattern change detector is designed to improve the tracking response of the autonomous Kalman filter. With such setting, the SRLP algorithm identifies those periods of time when the user's moving pattern is well described by the behavior model. For these periods, the SRLP algorithm automatically switches the receiver into a power saving mode and periodically wakes up the receiver to exam the validity of the behavior model. To reduce the overhead associated with these validity checks, a code phase prediction algorithm is also designed.; Experiments were performed to verify the effectiveness of the SRLP algorithm. It is found that a reduction of 65% in duty cycle is achievable. This figure is expected to be lowered by another factor of I0 if the code phase prediction algorithm can be implement. Therefore, by adaptively adjusting the receiver duty cycle to match the moving behavior of GPS users, we have developed a SRLP algorithm which effectively reduces the power consumption without compromising the accuracy of the position reported.