New detectors and detector architectures for high resolution optical sensor systems

The department of Optical Information Systems (OS) at the Institute of Robotics and Mechatronics of the German Aerospace Center (DLR) has more than 25 years experience with high-resolution imaging technology. The technology changes in the development of detectors, as well as the significant change of the manufacturing accuracy in combination with the engineering research define the next generation of spaceborne sensor systems focusing on Earth observation and remote sensing. The combination of large TDI lines, intelligent synchronization control, fast-readable sensors and new focal-plane concepts open the door to new remote-sensing instruments. This class of instruments is feasible for high-resolution sensor systems regarding geometry and radiometry and their data products like 3D virtual reality. Systemic approaches are essential for such designs of complex sensor systems for dedicated tasks. The system theory of the instrument inside a simulated environment is the beginning of the optimization process for the optical, mechanical and electrical designs. Single modules and the entire system have to be calibrated and verified. Suitable procedures must be defined on component, module and system level for the assembly test and verification process. This kind of development strategy allows the hardware-in-the-loop design. The paper gives an overview about the current activities at DLR in the field of innovative sensor systems for photogrammetric and remote sensing purposes.

This paper presents an optical fibre pressure and temperature sensor (OFPTS) system, which is adapted for use as a urodynamic pressure measurement system (UPS) for differential pressure measurement with temperature compensation. The OFTPS is based on a Fabry Perot interferometer (FPI), which acts as a pressure sensor and includes an embedded fibre Bragg grating (FBG) for temperature measurement. The sensor system is evaluated in a lower urinary tract (LUT) simulator, which simulates the bladder, rectum and detrusor muscle. The system was benchmarked against a commercially available urodynamic system, at the University Hospital Limerick (UHL) Urology Clinic. Both systems demonstrate a high correlation with a relative pressure variation of less than ±2.8cmH₂O for abdominal and ±4cmH₂O for vesical pressure. The repetitive measurement of the OFPTS system in the LUT simulator against the commercial system demonstrated the high repeatability. Furthermore, the low fabrication cost makes the OFPTS a potentially interesting instrument for urodynamic and other medical applications.

We explain the technologies used for high-performance long linear arrays based on HgCdTe/CMOS hybrid multiplexers with bidirectional time delay and integration (TDI) functions and describe the development of the first high-resolution IR imaging system with a superextended graphics array (SXGA) format. Long-wavelength IR photodiode arrays are fabricated using liquid-phase epitaxially grown HgCdTe on a CdZnTe substrate. Each photodiode array consists of 480x8 element n+/n-on-p diodes formed by B+ implantation. Diodes with a 10.3-μm cutoff wavelength have a typical zero-bias resistance of 10 MΩ and a shunt resistance of 1 GΩ. Four CMOS readout integrated circuits (ROICs) are used for bidirectional TDI and multiplex operations, where each ROIC sums up and multiplexes eight signals from 120 channels. The ROIC also includes pixel deselection and gain control circuits along with the corresponding memory and writing means. The IR focal plane arrays (IRFPAs) have a typical noise equivalent temperature difference (NETD) of 18 mK after TDI with F/1.55 optics and 10-μs integration. The IR imaging system adopts an interlace scan using the 480x8 element IRFPA to demonstrate a high spatial resolution of 1280 horizontal lines by 960 vertical lines (SXGA format) and an NETD of less than 30 mK. The unique algorithm for image enhancement is successfully confirmed to be efficient.

As an important member of optical fiber sensor, fiber optic Extrinsic Fabry-Perot Interferometric (EFPI) sensor has prospects for a wide range of industrial applications due to its small size, compact configuration, good reliability and flexibility. In a white light based fiber optic EFPI sensor system, which has the advantages of large dynamic range and high resolution, spectral analysis equipment is the most important part which takes the major cost of the system. Therefore, multiplexing spectral analysis equipment to measure multiple sensors simultaneously is an effective and necessary way that can save the cost of the whole sensor system. In this paper, a scheme based on the frequency division multiplexing of EFPI optical fiber sensors is proposed. Two EFPI sensors with different gap lengths are parallely connected through the optical fiber coupler. The overlapped interference spectrum of the two EFPI sensors is measured by using an optical spectrum analyzer, which is separated into two individual interference spectrums with a Finite Impuse Response (FIR) band-pass filter. Their envelope components are extracted with Hilbert transform, and then the interference spectrums are normalized by the envelope components. The respective gap lengths of the two EFPI sensors are achieved with the cross correlation calculation. Using this frequency division spectral analysis method, a two-channel multiplexing EFPI sensor system is implemented in the laboratory. The deployment of this frequency division multiplexing technology can greatly reduce the cost of the whole system which has extensive potential applications for distributed fiber optic EFPI sensor system.

There are numerous types of fiber optic sensors and sensor systems that rely on the use of detector arrays to determine sensor output from returned optical signals. Spectrally modulating sensors such as those based on Bragg gratings and Fabry-Perot sensors based on white light interferometry are but two examples. One problem with such systems is often the resolution of the detector array. In this paper, experimental confirmation of a new technique is presented in which the signal from one or more sensors can be demodulated with high resolution. In the technique, the conventional detection system utilizing a linear detector array is replaced by a rotated 2-D digital camera. This results in a much higher sampling resolution than is obtained via linear sampling due to the "folding" of the detector array elements relative to the linearly varying parameter filter directly in front of the array. A theoretical description of the technique is given and its experimental validation is presented.

This work discusses remote fiber sensors enabled by optical amplification. Continuous wave numerical modeling based on the propagation of pumps and signal lasers coupled to optical fibers explores Raman amplification schemes to predict the sensor’s behavior. Experimental analyses report the results to a temperature remote optical sensor with 50 km distance between the central unit and the sensor head. An electrical interrogation scheme is used due to their low cost and good time response. Different architectures in remote sensor systems are evaluated, where diffraction gratings are the sensor element. A validation of calculated results is performed by experimental analyses and, as an application, the noise generated by Raman amplification in the remote sensors systems is simulated applying such numerical modeling. The analyses of sensors systems based on diffraction gratings requires optical broadband sources to interrogate the optical sensor unit, mainly in long period gratings that shows a characteristic rejection band. Therefore, the sensor distance is limited to a few kilometers due to the attenuation in optical fibers. Additional attenuation is introduced by the sensor element. Hence, to extend the distance in the optical sensor system, the optical amplification system is needed to compensate the losses in the optical fibers. The Raman amplification technology was selected mainly due to the flexibility in the gain bandwidth. The modeling can be applied to sensor systems that monitor sites located at long distances, or in places that the access is restricted due to harsh environment conditions in such cases conventional sensors are relatively fast deteriorated.

A 2048 x 16 pixel time delay and integrate (TDI) monolithic focal plane array detector using PtSi Schottky barrier photodiodes and an interline CCD architecture was developed. A high resolution was achieved by using 30-micron pixels, with a high sensitivity through the TDI mode of operation. A ripple clocked vertical shift register was used for higher charge capacity, allowing a 43-percent fill factor with a saturated charge capacity of 530,000 electrons.

Sensor technology has been applied widely. Optical fiber sensor has lots of advantages: high sensitivity, long measurement length, high geometric plasticity, has become a hot research topic in sensor technology. Since modern industrial depends on temperature measurement at a large extent, it is significant for the research of optical fiber temperature sensor system. In this paper, the implementation of algorithm used in distributed optical fiber sensor system was discussed.

This paper reports on a novel solution for a transimpedance amplifier (TIA) specifically designed as an analog conditioning circuit for low-voltage, low-power, wearable, portable and implantable optoelectronic integrated sensor systems in biomedical applications. The growing use of sensors in all fields of industry, biomedicine, agriculture, environment analysis, workplace security and safety, needs the development of small sensors with a reduced number of electronic components to be easily integrated in the standard CMOS technology. Especially in biomedicine applications, reduced size sensor systems with small power consumption are of paramount importance to make them non-invasive, comfortable tools for patients to be continuously monitored even with personalized therapeutics and/or that can find autonomous level of life using prosthetics. The proposed new TIA architecture has been designed at transistor level in TSMC 0.18 μm standard CMOS technology with the aim to operate with nanoampere input pulsed currents that can be generated, for example, by Si photodiodes in optical sensor systems. The designed solution operates at 1.8 V single supply voltage with a maximum power consumption of about 36.1 μW and provides a high variable gain up to about 124 dBΩ (with fine- and coarse-tuning capabilities) showing wide bandwidth up to about 1.15 MHz and low-noise characteristics with a minimum noise floor level down to about 0.39 pA/Hz. The overall circuit is described in detail, and its main characteristics and performances have been analyzed by performing accurate post-layout simulations.

An air–oil and oil–water interface detector composed of bent plastic optical fiber, photodiode, light emitting diode (LED) and five analog electric circuits was developed and the sensor system was applied to measurement of the oil layer thickness of kitchen wastewater in a grease trap (oil separator for industrial kitchen wastewater). The raw output voltage of the developed sensor system depends on the refractive indexes of the air, soybean oil and tap water. When the sensitive part of the sensor passes through the oil layer, the air–oil and oil–water interfaces can be detected by the peak of the first derivative data calculated from the output voltage of the sensor system. The optimal sampling interval of the output voltage and the optimal movement speed of the sensor are between 100 and 400 ms and over 2.56 mm/s, respectively. The detection limit of oil layer thickness is approximately 3 mm at a 100 ms sampling interval and 2.56 mm/s movement speed. To evaluate the developed sensor system, the thickness of the oil layer in the actual wastewater was measured. Good agreement between the conventional analysis value obtained by a hexane extraction method and the calculated value obtained by the developed sensor was observed. The developed plastic optical fiber sensor system is useful to measure the amount of the floating oil (oil layer thickness) in a grease trap installed in the stream of the wastewater discharged from an industrial kitchen, and the sensor materials are very cheap. A sensing system for detecting the interface of the various materials can be constructed because the refractive index of the materials may be detectable by the developed sensor.

In this paper, the analysis of sensor results from a light emitting diode (LED) based optical fiber sensor (OFS) system is presented. A tri-color RGB (Red-Green-Blue) LED is used to provide three stimulus colors to stimulate a Surface Plasmon Resonance (SPR) sensor which is optically coupled to the system electronics. Analysis of the sensor results under different light conditions is used to identify a particular chemical under test. In the analysis approach undertaken, a combination of the CURE (Clustering Using REpresentatives) data clustering method (algorithm) and the k-nearest neighbor (kNN) algorithm is used for classifying the chemical under test. The system hardware is based on the field programmable gate array (FPGA) and the classification is undertaken on a personal computer (PC) using the Python open source programming language.

Hetero-core spliced optical fiber SPR sensor system for soil gravity water monitoring in agricultural environments

Smart optical sensor systems in CMOS for measuring light intensity and colour

<abstract> <bold><sc>Abstract.</sc></bold> This study evaluated four optical sensor systems in an effort to characterize a robust nondestructive technique to estimate tree-specific oil palm leaflet nutrient deficiency and aid in determining the required fertilizer dosage rates. The four sensor systems used were a handheld reflectance sensor (GreenSeeker 505), a chlorophyll meter (SPAD 502 Plus), a fluorescence sensor (Multiplex 3), and a spectroradiometer (FieldSpec 3). Spectral responses were collected using the above sensors for leaf samples from 164 randomly selected trees from three commercial farms in Malaysia. The spectral data were processed using either stepwise multiple linear regression (SMLR) or rank features techniques for feature extraction. The feature datasets were analyzed using support vector machine (SVM), soft independent modeling of class analogies (SIMCA), and artificial neural network (ANN) classifiers. The SVM and ANN classifiers performed better compared to SIMCA for most nutrient prediction cases. Overall, with SMLR as a feature extraction technique and SVM as a classifier, a spectroradiometer can be used to effectively predict N, P, K, Mg, Ca, and B nutrient levels in oil palm leaflets. The average overall prediction accuracies for the above conditions were in the range of 59% to 85%. The spectroradiometer dataset was further analyzed using SVM regression models for estimating nutrient levels. Either SMLR-selected features or partial least square (PLS) latent variables were used for establishing the above regression models. The models fitted on the SMLR features performed better for N, Mg, Ca, and B, with correlation coefficients (r) for test datasets in the range of 0.45 to 0.78. The best fitted SVM regression models were for boron estimation, with a correlation coefficient of 0.78 and root mean squared error of prediction (RMSEP) of 2.82.

New Sensor Application in European Industries for Detailed Bioprocess Monitoring