Data acquisition and signal conditioning for low power measurement systems

by Kozmin, Kirill, PhD

Abstract (Summary)
Integrated circuit (IC) power consumption and die are two important parameters that can define its cost as well as performance. That is why these two topics remain very important both in industry and in the research community. The fact that many ICs are designed to work in autonomous electronic devices with a limited power supply makes power consumption a particularly important issue. The main focus of this thesis is to investigate how specific signal properties can be utilized in the design of power efficient, small die area data acquisition and signal conditioning systems. In a signal acquisition system, three main parts can typically be identified: signal sensing and conditioning, signal processing, and communication. All of these parts consume energy. To reduce power consumption, different strategies can be used. For instance, the parts that are unused can be shut down. Another strategy is to use an event driven approach for hardware design. In this approach, the necessary parts of the acquisition system are enabled in response to external or internal events. The present thesis shows how an event driven approach can be utilized in hardware design in an example of level-crossing ADC, where sampling moments are triggered by the signal itself. The thesis presents a design procedure for the level-crossing ADC. Constraints for each building block are identified in system level simulations, performed in Cadence and MATLAB. A particular focus was put on the design of a comparator -- one of the ADC blocks. One of the main parameters for the comparator, in the context of the level-crossing ADC, is the propagation delay stability. The thesis discusses several techniques, which can be used to improve the propagation delay stability. Furthermore, two comparator implementations are presented. System simulations show the feasibility of the level-crossing ADC. They also show that such an ADC has a potential to reach smaller required die area and power consumption in the range of state of the art conventional ADCs. Another example of the signal properties utilization, in order to reach a smaller design area, presented in the thesis is in a navigation system for mobile robots. The navigation system consists of CMOS image sensors, an infra-red flash, and reflecting beacons placed vertically on walls. After an image is taken, the beacons are detected on the image and the position of the robot is calculated. The vertical positioning of the beacons allows minimization of the computational effort for their detection in the image. The image sensor optics, however, introduces image distortion, which can result in systematic calculation error. The distortion can be calibrated and eliminated after the image is taken. This, however, requires some computation power, which can be unavailable either due to complexity or calculation time constraints. Therefore, a precalculated model can be stored in memory and applied later on. This approach, however, requires a large amount of memory. To reduce the required memory size, a compression algorithm based on distortion model properties is presented in the thesis. The algorithm allows reduction of the required memory by more than 100 times.
Bibliographical Information:


School:Luleå tekniska universitet

School Location:Sweden

Source Type:Doctoral Dissertation



Date of Publication:01/01/2008

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