The paper presents a novel implementation of a time-to-digital converter (TDC) in field-programmable gate array (FPGA) devices. The design employs FPGA digital signal processing (DSP) blocks and gives more than two-fold improvement in mean resolution in comparison with the common conversion method (carry chain-based time coding line). Two TDCs are presented and tested depending on DSP configuration. The converters were implemented in a Kintex-7 FPGA device manufactured by Xilinx in 28 nm CMOS process. The tests performed show possibilities to obtain mean resolution of 4.2 ps but measurement precision is limited to at most 15 ps mainly due to high conversion nonlinearities. The presented solution saves FPGA programmable logic blocks and has an advantage of a wider operation range when compared with a carry chain-based time coding line.
A new time interval/frequency generator with a jitter below 5 ps is described. The time interval generation mechanism is based on a phase shifting method with the use of a precise DDS synthesizer. The output pulses are produced in a Spartan-6 FPGA device, manufactured by Xilinx in 45 nm CMOS technology. Thorough tests of the phase shifting in a selected synthesizer are performed. The time interval resolution as low as 0.3 ps is achieved. However, the final resolution is limited to 500 ps to maximize precision. The designed device can be used as a source of high precision reference time intervals or a highly stable square wave signal of frequency up to 50 MHz.
Raman spectrometers are devices which enable fast and non-contact identification of examined chemicals. These devices utilize the Raman phenomenon to identify unknown and often illicit chemicals (e.g. drugs, explosives) without the necessity of their preparation. Now, Raman devices can be portable and therefore can be more widely used to improve security at public places. Unfortunately, Raman spectra measurements is a challenge due to noise and interferences present outside the laboratories. The design of a portable Raman spectrometer developed at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology is presented. The paper outlines sources of interferences present in Raman spectra measurements and signal processing techniques required to reduce their influence (e.g. background removal, spectra smoothing). Finally, the selected algorithms for automated chemicals classification are presented. The algorithms compare the measured Raman spectra with a reference spectra library to identify the sample. Detection efficiency of these algorithms is discussed and directions of further research are outlined.