Mohan Shankar

Human Tracking With Wireless Distributed Pyroelectric Sensors

This paper presents a wireless pyroelectric sensor system, composed of sensing modules (slaves), a synchronization and error rejection module (master), and a data fusion module (host), to perform human tracking. The computation workload distribution among slave, master, and host is investigated. The performances and costs of different signal-processing and target-tracking algorithms are discussed. A prototype system is described containing pyroelectric sensor modules that are able to detect the angular displacement of a moving thermal target. Fresnel lens arrays are used to modulate the sensor field of view. The sensor system has been used to track a single human target

Human-tracking systems using pyroelectric infrared detectors

We design and develop a low-cost pyroelectric detector- based IR motion-tracking system. We study the characteristics of the detector and the Fresnel lenses that are used to modulate the visibility of the detectors. We build sensor clusters in different configurations and demonstrate their use for human motion tracking.

Thin infrared imaging systems through multichannel sampling

The size of infrared camera systems can be reduced by collecting low-resolution images in parallel with multiple narrow-aperture lenses rather than collecting a single high-resolution image with one wide-aperture lens. We describe an infrared imaging system that uses a three-by-three lenslet array with an optical system length of 2.3 mm and achieves Rayleigh criteria resolution comparable with a conventional single-lens system with an optical system length of 26 mm. The high-resolution final image generated by this system is reconstructed from the low-resolution images gathered by each lenslet. This is accomplished using superresolution reconstruction algorithms based on linear and nonlinear interpolation algorithms. Two implementations of the ultrathin camera are demonstrated and their performances are compared with that of a conventional infrared camera.

Path-dependent human identification using a pyroelectric infrared sensor and Fresnel lens arrays

This paper presents a design and development of a low power consumption, and low cost, human identification system using a pyroelectric infrared (PIR) sensor whose visibility is modulated by a Fresnel lens array. The optimal element number of the lens array for the identification system was investigated and the experimental results suggest that the lens array with more elements can yield a better performance in terms of identification and false alarm rates. The other parameters of the system configuration such as the height of sensor location and sensor-to-object distance were also studied to improve spectral distinctions among sensory data of human objects. The identification process consists of two parts: training and testing. For the data training, we employed a principal components regression (PCR) method to cluster data with respect to different registered objects at different speed levels. The feature data of different objects walking along the same path in training yet at random speeds are then tested against the pre-trained clusters to decide whether the target is registered, and which member of the registered group it is.

Compressive video sensors using multichannel imagers

We explore the possibilities of obtaining compression in video through modified sampling strategies using multichannel imaging systems. The redundancies in video streams are exploited through compressive sampling schemes to achieve low power and low complexity video sensors. The sampling strategies as well as the associated reconstruction algorithms are discussed. These compressive sampling schemes could be implemented in the focal plane readout hardware resulting in drastic reduction in data bandwidth and computational complexity.

Lightweight biometric detection system for human classification using pyroelectric infrared detectors

We use pyroelectric detectors that are differential in nature to detect motion in humans by their heat emissions. Coded Fresnel lens arrays create boundaries that help to localize humans in space as well as to classify the nature of their motion. We design and implement a low-cost biometric tracking system by using off-the-shelf components. We demonstrate two classification methods by using data gathered from sensor clusters of dual-element pyroelectric detectors with coded Fresnel lens arrays. We propose two algorithms for person identification, a more generalized spectral clustering method and a more rigorous example that uses principal component regression to perform a blind classification.

Ultra-thin multiple-channel LWIR imaging systems

Infrared camera systems may be made dramatically smaller by simultaneously collecting several low-resolution images with multiple narrow aperture lenses rather than collecting a single high-resolution image with one wide aperture lens. Conventional imaging systems consist of one or more optical elements that image a scene on the focal plane. The resolution depends on the wavelength of operation and the f-number of the lens system, assuming a diffraction limited operation. An image of comparable resolution may be obtained by using a multi-channel camera that collects multiple low-resolution measurements of the scene and then reconstructing a high-resolution image. The proposed infrared sensing system uses a three-by-three lenslet array with an effective focal length of 1.9mm and overall system length of 2.3mm, and we achieve image resolution comparable to a conventional single lens system having a focal length of 5.7mm and overall system length of 26mm. The high-resolution final image generated by this system is reconstructed from the noisy low-resolution images corresponding to each lenslet; this is accomplished using a computational process known as superresolution reconstruction. The novelty of our approach to the superresolution problem is the use of wavelets and related multiresolution method within a Expectation-Maximization framework to improve the accuracy and visual quality of the reconstructed image. The wavelet-based regularization reduces the appearance of artifacts while preserving key features such as edges and singularities. The processing method is very fast, making the integrated sensing and processing viable for both time-sensitive applications and massive collections of sensor outputs.

On-orbit stability and performance of the Clouds and Earth’s Radiant Energy System (CERES) instrument sensors onboard the Aqua and Terra Spacecraft

The Clouds and Earth’s Radiant Energy System (CERES) instruments onboard the Terra and Aqua spacecraft are part of the NASA Earth Observing System (EOS) constellation to make long-term observations of the earth. CERES measures the earth-reflected shortwave energy as well as the earth-emitted thermal energy, which are two components of the earth’s radiation energy budget. These measurements are made by five instruments- Flight Models (FM) 1 and 2 onboard Terra, FMs 3 and 4 onboard Aqua and FM5 onboard Suomi NPP. Each instrument comprises three sensors that measure the radiances in different wavelength bands- a shortwave sensor that measures in the 0.3 to 5 micron band, a total sensor that measures all the incident energy (0.3-200 microns) and a window sensor that measures the water-vapor window region of 8 to 12 microns. The stability of the sensors is monitored through on-orbit calibration and validation activities. On-orbit calibration is carried out using the Internal Calibration Module (ICM) that consists of a tungsten lamp, blackbodies, and a solar diffuser known as the Mirror Attenuator Mosaic (MAM). The ICM calibration provides information about the stability of the sensors’ broadband radiometric gains on-orbit. Several validation studies are conducted in order to monitor the behavior of the instruments in various spectral bands. The CERES Edition-4 data products for FM1-FM4 incorporate the latest corrections to the sensor responses using the calibration techniques. In this paper, we present the on-orbit performance stability as well as some validation studies used in deriving the CERES Edition-4 data products from all four instruments.

Pre-launch characterization of spectral response functions for the Clouds and Earth's Radiant Energy System (CERES) instrument sensors

The Clouds and Earths Radiant Energy System (CERES) uses four instruments onboard two spacecraft to make measurements of the earths reflected shortwave and emitted longwave radiation, which constitute two components of earth radiation budget. Flight Models 1 and 2 (FM1, FM2) are onboard the TERRA spacecraft and Flight Models 3 and 4 (FM3, FM4) are onboard the AQUA spacecraft. The measurements are made using three radiometric sensor channels on each instrument- shortwave channel (0.3-5 microns), window channel (8-12 microns) and total channel (0.3-200 microns). This paper describes the process of obtaining the estimates of the spectral response functions of the three sensor channels using pre-launch measurements. The shortwave spectral response function (0.3-2 microns) for the shortwave channel as well as the shortwave region of the total channel is obtained through measurements of the components in the optical path. The longwave responses (>2 microns) are obtained using a Fourier Transform Spectrometer (FTS) system. The CERES sensors as well as a reference detector, which is used to account for any measurement or background noise in the system, acquire measurements of the FTS. By the use of various sources and beam-splitters in the spectrometer, the entire spectral range of the broadband total channel is covered. The spectral estimates are obtained in smaller, overlapping bands, which are then tied together appropriately to obtain the end-to-end spectral response function for each of the sensors for all CERES instruments.

Biometric tracking with coded pyroelectric sensor clusters

Human bodies are very good heat sources with peak emission wavelength of about 9?m. We use pyroelectric detectors that are differential in nature to detect human motion by their heat emissions. Coded Fresnel lens arrays create boundaries in space which helps to localize the human motion as well as classification. We design and implement a low-cost biometric tracking system using off-the-shelf components. We demonstrate tracking and classification using sensor clusters of dualelement pyroelectric detectors with coded Fresnel lens arrays.