With today’s technology, digital signal processing plays a major role. It is used widely in many applications. Many applications require high resolution in measured data to achieve a perfect digital processing technology. The key to achieve high resolution in digital processing systems is analog-to-digital converters. In the market, there are many types ADC for different systems. Delta-sigma converters has high resolution and expected speed because it’s special structure. The signal-to-noise-and-distortion (SINAD) and total harmonic distortion (THD) are two important parameters for delta-sigma converters. The paper will describe the theory of parameters and test method.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / For research purposes on helicopter rotor acoustics a large data acquisition system called TEDAS (Transputer based Expandable Data Acquisition System) has been developed. The key features of this system are: unlimited expandability and sum data rate, local storage of data during operation, very simple analog anti aliasing filtering due to extensive digital filtering, and integrated computational power which scales with the number of channels. The sample rate is up to 50 kHz/channel, the resolution is 16 bit, 360 channels are realized now. TEDAS consists of blocks with 8 A/D converters which are controlled by one transputer T800. The size of the local memory is 4 Mbyte. Any number of blocks (IDAM = Intelligent Data Acquisition Module) can be combined to a complete system. Data preprocessing is done in parallel inside the IDAMs. As for 16 bit systems the analog antialiasing filtering becomes a dominant factor of the costs, delta sigma ADCs with oversampling and internal digital filtering are used. This produces an exact linear phase and a stop band rejection of -90 dB.

In present day, digital signal processing (DSP) is a popular technology and widely used in many fields. There have increasing number of applications that need high resolution converters. Therefore, analog-to-digital converters play a major role in DSP, and a well-performed ADC will enhance the performance of a certain system. Different types of ADCs are available for various functions. Delta-sigma  converters are famous for high resolution. Dynamic parameters can be used to judge the performance of an ADC, this paper will focus on the critical parameters of spectrum analysis, which contains Signal-to-Noise-and-Distortion Ratio (SINAD), Effective Number of Bits (ENOB) and Spurious-free Dynamic Range (SFDR). The theory and test method of these critical parameters are proposed in this paper using the Evaluation Module and Matlab. The results we acquired from the Evaluation Module are SINAD=86.15dB, SFDR=109.2dB, ENOB=14.177bits; and the results we calculated from MATLAB are: SINAD=86.14dB, SFDR=108.8dB, ENOB=14bits.

This dissertation presents a comprehensive design and analysis framework for system-on-a-chip analog-to-digital conversion design. The design encompasses a broad class of systems, which take advantage of system-on-a-chip complexity. This class is exemplified by an interferometric photodetector array based bio-optoelectronic sensor that is built and tested as part of the reported work. While there have been many discussions of the technical details of individual analog-to-digital converter (ADC) schemes in the literature, the importance of the analog front-end as a pre-processor for a data converter and the generalized analysis including converter encoding and decoding functions have not previously been investigated thoroughly, and these are key elements in the choice of converter designs for low-noise systems such as bio-optoelectronic sensors. Frequency domain analog front-end models of ADCs are developed to enable the architectural modeling of ADCs. The proposed models can be used for ADC statistically worst-case performance estimation, with stationary random process assumptions on input signals. These models prove able to reveal the architectural advantages of a specific analog-to-digital converter schemes quantitatively, allowing meaningful comparisons between converter designs. The modeling of analog-to-digital converters as communication channels and the ADC functional analysis as encoders and decoders are developed. This work shows that analog-to-digital converters can be categorized as either a decoder-centered design or an encoder-centered design. This perspective helps to show the advantages of nonlinear decoding schemes for oversampling noise-shaping data converters, and a new nonlinear decoding algorithm is suggested to explore the optimum solution of the decoding problem. A case study of decoder-centered and encoder-centered data converter designs is presented by applying the proposed theoretical framework. The robustness and flexibility of the resulting analog-to-digital converters are demonstrated and compared. The electrical and optical sensitivity measurements of a fabricated oversampling noise shaping analog-to-digital converter circuit are provided, and a sensor system-on-a-chip using these ADCs with integrated interferometric waveguides for bio-optoelectronic sensing is demonstrated.