2002 NVTherm improvements

Maurer, Tana; Driggers, Ronald G.; Vollmerhausen, Richard H.; Friedman, Melvin H.

doi:10.1117/12.477448

Cited by 9 publications

(8 citation statements)

References 4 publications

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“…A key parameter for indicating the strength of the atmospheric turbulence is the refractive index structure parameter, C 2 n , which was evaluated by transmitting the concerned mode and then calculating the scintillation index at the receiver using the intensity profile measurements from a charge-coupled-device camera. The scintillation index is given by the Rytov variance [62]:…”

Section: Methodsmentioning

confidence: 99%

Post-Flood UAV-Based Free Space Optics Recovery Communications with Spatial Mode Diversity

et al. 2022

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The deployment of unmanned aerial vehicles (UAVs) for free space optical communications is an attractive solution for forwarding the vital health information of victims from a flood-stricken area to neighboring ground base stations during rescue operations. A critical challenge to this is maintaining an acceptable signal quality between the ground base station and UAV-based free space optics relay. This is largely unattainable due to rapid UAV propeller and body movements, which result in fluctuations in the beam alignment and frequent link failures. To address this issue, linearly polarized Laguerre–Gaussian modes were leveraged for spatial mode diversity to prevent link failures over a 400 m link. Spatial mode diversity successfully improved the bit error rate by 38% to 55%. This was due to a 10% to 19% increase in the predominant mode power from spatial mode diversity. The time-varying channel matrix indicated the presence of nonlinear deterministic chaos. This opens up new possibilities for research on state-space reconstruction of the channel matrix.

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Section: Methodsmentioning

confidence: 99%

Post-Flood UAV-Based Free Space Optics Recovery Communications with Spatial Mode Diversity

et al. 2022

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“…The novel TA approach seem to be the same as the previous TA models in the calculation process, but have distinct differences in nature. The previous TA model only Spatial Frequency Sr (1/mrad) needs calculate the discrimination range corresponding to a single apparent differential temperature of the total target/background, as is illustrated in Reference [1]. While for the novel TA model, all the angular spatial frequencies corresponding to the apparent differential temperature of different sub regions need to be obtained, respectively, as shown in Fig.…”

Section: Novel Approach Of Ta Performance Predictionmentioning

confidence: 99%

“…Many TA models [1][2][3] have been developed and improved in the past few years. Owing to a number of widely known practical and theoretical problems relating to the measurement and application of the MRTD curve [4], P.Bijl et al [5][6][7][8][9][10][11] introduced a new measurement-the TOD curve for infrared imaging system characterization.…”

Section: Introductionmentioning

confidence: 99%

Field Performance Prediction Method Based On Contrast Metric Of Target Sub Regions

Wang

Liu

Zhang

2007

Int J Infrared Milli Waves

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The field performance prediction of infrared imaging system is an important subject in infrared imaging field. In this paper, a novel method for predicting TA (target acquisition) performance is proposed, which combines the TOD (triangle orientation discrimination) threshold curve with an improved contrast metric based on the temperature in target sub regions. Specifically, the target is first subdivided into some sub regions with different target/background differential temperatures according to its thermal structure distribution. The number of equivalent triangle patterns across each sub region is calculated utilizing its effective size, the apparent temperature difference line, and the TOD curve. Further, the total number of equivalent triangle patterns over the integral target is achieved. Combining the TOD criteria, the target acquisition ranges for different discrimination (detection, recognition, and identification) levels are obtained by solving a set of equations. Comparisons with the preliminary experimental results show that this new TA approach can provide reasonable prediction of field performance.

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“…From Johnson's criteria one can then determine the detection, recognition and identification ranges. NVTherm provides accurate predictions of sensor performance for both well-sampled and under-sampled thermal imagers [30]. The output from NVTherm can be used in many different ways.…”

Section: Modelmentioning

confidence: 99%

Comparison of modeled atmosphere-dependent range performance of long-wave and mid-wave IR imagers

Dhar

Khan

2008

Infrared Physics & Technology

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2002 NVTherm improvements

Cited by 9 publications

References 4 publications

Post-Flood UAV-Based Free Space Optics Recovery Communications with Spatial Mode Diversity

Post-Flood UAV-Based Free Space Optics Recovery Communications with Spatial Mode Diversity

Field Performance Prediction Method Based On Contrast Metric Of Target Sub Regions

Comparison of modeled atmosphere-dependent range performance of long-wave and mid-wave IR imagers

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