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We propose a sensor for Advance Driver Assistance Systems (ADAS) with unique properties in terms of measuring time and distance that are necessary to predict the pavement condition several meters ahead of a moving vehicle.

We propose an optical thickness measurement device based on electro-optic dual-optical frequency combs (dual-OFCs). Optical frequency combs (OFCs) are light sources that provide an optical signal consisting of many equidistant monochromatic tones. In this paper, we present an agile dual-OFC architecture with adjustable frequency separation of the comb modes and total frequency span, allowing high-resolution measurements of the thickness of transparent thick samples. This architecture is based on a single continuous-wave laser diode and external electro-optic devices to implement the dual-comb sensor, allowing easy control of the optical spectrum of the interrogation source (dual-OFC). As it is characteristic of dual-OFC systems, the optical transmittance function of the sample (etalon) is directly translated to the radiofrequency domain, where detection, demodulation, and processing of signals are performed. The shift in the complexity of implementation from the optical to the electronic domain yields many advantages, as acquisition and signal processing are made independently on the optical characteristics of the sample (thickness). This work was supported by the Spanish Ministry of Economy and Competitiveness under the RTC-2015-4205-4 Salicar and TEC-2014-52147-R Mossi grants.

Optical frequency combs (OFCs) generated through the modulation of continuous-wave lasers offer higher power per component, simple comb spacing control, and lower complexity and cost than traditional OFCs. By these reasons, they are an interesting optical source for spectrometers. In this letter, a dual-comb architecture based on two OFCs generated from the same laser using optical phase modulators is presented. The system features a new placement for the spectroscopic sample that increases the versatility, robustness, and stability of the instrument without requiring any reconfiguration for carrying out different types of measurement. Besides this, a self-referenced detection setup based on digital phase sensitive multitone detection improves the SNR of the previous approaches offering more flexibility in its configuration and high data output rate. The proposed architecture is validated by measuring a ro-vibrational absorption feature of HCN at 1544.51 nm and characterizing the spectral response of a fiber-coupled Fabry–Perot filter.

We describe a fiber laser interferometer that has been designed with the purpose of non-invasive continuous fetal heart rate monitoring. The measuring principle is based on the measurement of the arterial wave of a fetus from the arterial pulse wave of a pregnant patient, so the application requires the measurement of arterial pulse waves with very high resolution. The main characteristics of the specific application interferometer are: First, it is based on a common path topology in order to simplify the design of the non-contact optical probe to place on the body of the patient. Second, it uses a low power semiconductor laser at a safe operating wavelength of 1,55 μm. Third, a phase modulation with digital demodulation scheme is used in order to increase range and resolution simultaneously. The resulting interferometer provides up to 1 nm resolution and one millimeter range. Results showing arterial pulse waves measured on the wrist and a finger nail of a patient are presented.

A sensitive optical microphone for photoacoustic spectroscopy based on the common path topology of a fibre laser Doppler vibrometer (FLDV) using phase-generated carrier demodulation and a slim diaphragm as an acoustic wave transducer was demonstrated. A resonant gas cell was adapted to enhance gas-detection performance and simultaneously provide efficient cancellation of the window background acoustic signal. Ammonia (NH3) was selected as the target gas. The absorption line was experimentally identified using a distributed feedback laser diode emitting at 1530 nm. The linearity and sensitivity of the gas sensor were measured using wavelength modulation spectroscopy with second harmonic detection. A Teflon diaphragm was used to implement the optical microphone, along with the FLDV, showing a minimum detectable pressure of 79.5 &mu, Pa/Hz1/2. The noise-equivalent absorption sensitivity for NH3 detection at the absorption line at 1531.7 nm was 1.85 &times, 10&minus, 8 W cm&minus, 1 Hz&minus, 1/2, and the limit of detection was 785 ppbv.

In this paper a new laser range finder approach is presented. It is based on a fan of beams of different optical frequencies that are projected to the target. The detected back-reflected beams contain frequency-encoded information about its reflection angles, which are used for the calculation of the range by means of triangulation methods. The fan of beams is generated from a fieldable electro-optic dual optical frequency comb generator and a diffractive optical system, without any moving parts. A proof-of-concept prototype of a range finder based on this approach was implemented and experimentally tested. An analysis of main sources of errors is also presented.

In this paper we describe a fiber-based remote sensing device for the detection of liquid water and ice on the road surface suitable for on-board applications. The system is based on the different optical responses of water and ice to three near infrared wavelengths from low-cost semiconductor laser sources. The design of the sensor is divided in three main parts: The optical fiber-based illumination and collection optics, the optoelectronic system composed by the emitters/detector and the modulation/demodulation electronics and, finally, the data acquisition and digital processing system. The flexible optical design allows both the use of the sensor attached to a post by the road for static measurements, or to be incorporated into a road maintenance vehicle.

We describe the implementation of a vision system based on a hardware neural processor. The architecture of the neural network processor has been designed to exploit the computational characteristics of electronics and the communication characteristics of optics in an optimal manner, thus it is based on an optical broadcast of input signals to a dense array of processing elements. The vision system has been built by use of a prototype implementation of a neural network processor with discrete optic and optoelectronic devices. It has been adapted to work as a Hamming classifier of the images taken with a 128 x 128 complementary metal-oxide semiconductor image sensor. Its results, performance characteristics of the image classification system, and an analysis of its scalability in size and speed, with the improvement of the optoelectronic neural processor, are presented.

We present experimental and theoretical results obtained from the study of the effects of optical feedback in low-cost Fabry-Perot laser diodes due to the presence of an external cavity created by an external reflective or diffusive vibrating target. Experimental results show that a change in the length of the external cavity produces the well-known amplitude modulation of the optical output power and, depending on the amount of optical feedback, a subperiodicity appears in the amplitude modulation of the output power. The experiments show that the subperiodicity appears independently of the length of the external cavity and is due to mode hopping between different longitudinal laser modes. Numerical analysis focused on the effects observed support that the mode hop occurs between modes whose round-trip phase delay along the external cavity is out of phase, thus producing a subperiodicity of the total amplitude modulation.

We describe the concept of a vision system based on an optoelectronic hardware neural processor. The proposed system is composed of a pulse coupled neural network (PCNN) preprocessor stage that converts an input image into a temporal pulsed pattern. These pulses are inputs to the optical broadcast neural network (OBNN) processor, which classifies the input pattern between a set of reference patterns based on a pattern matching strategy. The PCNN is to provide immunity to the scale, rotation, and translation of objects in the image. The OBNN provides high parallelism and a high speed hardware neural processor.