60,013 research outputs found

    Multibeam single frequency synthetic aperture radar processor for imaging separate range swaths

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    A single-frequency multibeam synthetic aperture radar for large swath imaging is disclosed. Each beam illuminates a separate ""footprint'' (i.e., range and azimuth interval). The distinct azimuth intervals for the separate beams produce a distinct Doppler frequency spectrum for each beam. After range correlation of raw data, an optical processor develops image data for the different beams by spatially separating the beams to place each beam of different Doppler frequency spectrum in a different location in the frequency plane as well as the imaging plane of the optical processor. Selection of a beam for imaging may be made in the frequency plane by adjusting the position of an aperture, or in the image plane by adjusting the position of a slit. The raw data may also be processed in digital form in an analogous manner

    Characterization of modulated time-of-flight range image sensors

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    A number of full field image sensors have been developed that are capable of simultaneously measuring intensity and distance (range) for every pixel in a given scene using an indirect time-of-flight measurement technique. A light source is intensity modulated at a frequency between 10–100 MHz, and an image sensor is modulated at the same frequency, synchronously sampling light reflected from objects in the scene (homodyne detection). The time of flight is manifested as a phase shift in the illumination modulation envelope, which can be determined from the sampled data simultaneously for each pixel in the scene. This paper presents a method of characterizing the high frequency modulation response of these image sensors, using a pico-second laser pulser. The characterization results allow the optimal operating parameters, such as the modulation frequency, to be identified in order to maximize the range measurement precision for a given sensor. A number of potential sources of error exist when using these sensors, including deficiencies in the modulation waveform shape, duty cycle, or phase, resulting in contamination of the resultant range data. From the characterization data these parameters can be identified and compensated for by modifying the sensor hardware or through post processing of the acquired range measurements

    Time-resolved multi-mass ion imaging: femtosecond UV-VUV pump-probe spectroscopy with the PImMS camera

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    The Pixel-Imaging Mass Spectrometry (PImMS) camera allows for 3D charged particle imaging measurements, in which the particle time-of-flight is recorded along with (x,y)(x,y) position. Coupling the PImMS camera to an ultrafast pump-probe velocity-map imaging spectroscopy apparatus therefore provides a route to time-resolved multi-mass ion imaging, with both high count rates and large dynamic range, thus allowing for rapid measurements of complex photofragmentation dynamics. Furthermore, the use of vacuum ultraviolet wavelengths for the probe pulse allows for an enhanced observation window for the study of excited state molecular dynamics in small polyatomic molecules having relatively high ionization potentials. Herein, preliminary time-resolved multi-mass imaging results from C2_2F3_3I photolysis are presented. The experiments utilized femtosecond UV and VUV (160.8~nm and 267~nm) pump and probe laser pulses in order to demonstrate and explore this new time-resolved experimental ion imaging configuration. The data indicates the depth and power of this measurement modality, with a range of photofragments readily observed, and many indications of complex underlying wavepacket dynamics on the excited state(s) prepared

    Multiple frequency range imaging to remove measurement ambiguity

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    Range imaging systems use a specialised sensor to capture an image where object distance (range) is measured for every pixel using time-of-flight. The scene is illuminated with an amplitude modulated light source, and the phase of the modulation envelope of the reflected light is measured to determine flight time, hence object distance for each pixel. As the modulation waveform is cyclic, an ambiguity problem exists if the phase shift exceeds 2π radians. To overcome this problem we demonstrate a method that superposes two different modulation frequencies within a single capture. This technique reduces the associated overhead compared with performing two sequential measurements, allowing the system to retain high range measurement precision at rapid acquisition rates. A method is also provided to avoid interference from aliased harmonics during sampling, which otherwise contaminate the resulting range measurement. Experimental results show the potential of the multiple frequency approach; producing high measurement precision while avoiding ambiguity. The results also demonstrate the limitation of this technique, where large errors can be introduced through a combination of a low signal to noise ratio and suboptimal selection of system parameters

    Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset

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    Scene motion, multiple reflections, and sensor noise introduce artifacts in the depth reconstruction performed by time-of-flight cameras. We propose a two-stage, deep-learning approach to address all of these sources of artifacts simultaneously. We also introduce FLAT, a synthetic dataset of 2000 ToF measurements that capture all of these nonidealities, and allows to simulate different camera hardware. Using the Kinect 2 camera as a baseline, we show improved reconstruction errors over state-of-the-art methods, on both simulated and real data.Comment: ECCV 201

    Region-enhanced passive radar imaging

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    The authors adapt and apply a recently-developed region-enhanced synthetic aperture radar (SAR) image reconstruction technique to the problem of passive radar imaging. One goal in passive radar imaging is to form images of aircraft using signals transmitted by commercial radio and television stations that are reflected from the objects of interest. This involves reconstructing an image from sparse samples of its Fourier transform. Owing to the sparse nature of the aperture, a conventional image formation approach based on direct Fourier transformation results in quite dramatic artefacts in the image, as compared with the case of active SAR imaging. The regionenhanced image formation method considered is based on an explicit mathematical model of the observation process; hence, information about the nature of the aperture is explicitly taken into account in image formation. Furthermore, this framework allows the incorporation of prior information or constraints about the scene being imaged, which makes it possible to compensate for the limitations of the sparse apertures involved in passive radar imaging. As a result, conventional imaging artefacts, such as sidelobes, can be alleviated. Experimental results using data based on electromagnetic simulations demonstrate that this is a promising strategy for passive radar imaging, exhibiting significant suppression of artefacts, preservation of imaged object features, and robustness to measurement noise
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