Heinz Mattes

Optimal high-resolution spectral analyzer

This paper presents a new application field for the Goertzel algorithm. The test of mixed-signal circuits involves the generation and analysis of signals. A standard method for the signal analysis is the fast Fourier transform (FFT algorithms). Such complex algorithms are not suitable for BIST (built-in self-test) or BOST (built-off self-test) solutions due to their high demand for resources. In this paper, the Goertzel algorithm will be presented as an alternative to FFT algorithms. A new optimized structure of the Goertzel algorithm and its implementation in an FPGA (field programmable gate array) is presented. A comparison within the scope of the production test of RF transceiver devices shows a considerable reduction of the test time (factor 6) and resources (factor 10) compared to a FFT software solution respectively hardware solution.

Next Generation ADC Massive Parallel Testing with Real Time Parameter Evaluation

The paper describes the implementation of a novel Analog-to-Digital-Converter (ADC) test technique for next generation low cost massive parallel ADC testing using a Field Programmable Gate Array (FPGA) on tester load board. The goal is to test the ADC which is embedded in an automotive micro controller with only pure digital tester sources. Therefore, the analog test stimulus for the ADC is generated by using ΔΣ-modulation technique off-line and analog filtering on load board. The digital test response is analyzed by a FPGA in real time by comparing the measured data with a reference signal. The modular concept of FPGA evaluation allows for quick and flexible reaction on changing production test requirements. Simply by reprogramming the FPGA with a new module there is no need of any hardware reconfigurations. Measurements with a high precision reference ADC in laboratory environment show that the method is ready for production.

An approach to linear model-based testing for nonlinear cascaded mixed-signal systems

Linear Model-based Test and Diagnosis (MbT&D) has been successfully applied to single-block modules like Digital-to-Analog Converters (DACs) with a static non-linear transfer characteristic. For Multi-block modules, a diagnosis methodology is needed that can deal with cascades of several linear and nonlinear blocks. In contrast to non-linear methods, linear MbT&D methods only require matrix operations associated with relatively low computational effort. A modification of the linear MbT&D in combination with Volterra series is presented that can be applied to cascaded non-linear systems, for example, a DAC followed by a low-pass filter. A simultaneous identification of numerous frequency domain Volterra kernels is enabled, and thus, to test the compliance to data sheet specifications.