Thermal Signature Characteristics of Vehicle/Terrain Interaction Disturbances: Implications for Battlefield Vehicle Classification

地形 压实 环境科学 光谱特征 土壤压实 卡车 热的 地质学 遥感 采矿工程 岩土工程 工程类 汽车工程 气象学 物理 地理 地图学
作者
John W. Eastes,George L. Mason,Alan E. Kusinger
出处
期刊:Applied Spectroscopy [SAGE Publishing]
卷期号:58 (5): 510-515 被引量:2
标识
DOI:10.1366/000370204774103318
摘要

Thermal emissivity spectra (8–14 μm) of track impressions/background were determined in conjunction with operation of six military vehicle types, T-72 and M1 Tanks, an M2 Bradley Fighting Vehicle, a 5-ton truck, a D7 tractor, and a High Mobility Multipurpose Wheeled Vehicle (HMMWV), over diverse soil surfaces to determine if vehicle type could be related to track thermal signatures. Results suggest soil compaction and fragmentation/pulverization are primary parameters affecting track signatures and that soil and vehicle/terrain-contact type determine which parameter dominates. Steel-tracked vehicles exert relatively low ground-contact pressure but tend to fragment/pulverize soil more so than do rubber-tired vehicles, which tend mainly to compact. In quartz-rich, lean clay soil tracked vehicles produced impressions with spectral contrast of the quartz reststrahlen features decreased from that of the background. At the same time, 5-ton truck tracks exhibited increased contrast on the same surface, suggesting that steel tracks fragmented soil while rubber tires mainly produced compaction. The structure of materials such as sand and moist clay-rich river sediment makes them less subject to further fragmentation/pulverization; thus, compaction was the main factor affecting signatures in these media, and both tracked and wheeled vehicles created impressions with increased spectral contrast on these surfaces. These results suggest that remotely sensed thermal signatures could differentiate tracked and wheeled vehicles on terrain in many areas of the world of strategic interest. Significant applications include distinguishing visually/spectrally identical lightweight decoys from actual threat vehicles.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
心晴发布了新的文献求助10
1秒前
Hello应助马文采纳,获得10
2秒前
dde发布了新的文献求助10
3秒前
裴之洽闻发布了新的文献求助10
5秒前
田様应助jinzhen采纳,获得10
6秒前
兼听则明完成签到,获得积分10
6秒前
6秒前
6秒前
Wd发布了新的文献求助10
6秒前
熊二迷妹完成签到,获得积分10
7秒前
辛勤若云完成签到,获得积分10
7秒前
8秒前
yuki发布了新的文献求助10
11秒前
11秒前
棣月永远完成签到,获得积分10
12秒前
Singel发布了新的文献求助10
12秒前
李粉艳发布了新的文献求助10
12秒前
东方元语应助Jin采纳,获得20
13秒前
14秒前
Hwchaodoctor完成签到,获得积分10
15秒前
lizishu完成签到,获得积分0
16秒前
近是偏北的独完成签到,获得积分20
16秒前
jinzhen发布了新的文献求助10
17秒前
Lucas应助不是于谦采纳,获得10
17秒前
莫墨完成签到,获得积分10
17秒前
diyanbruker发布了新的文献求助10
17秒前
随机昵称发布了新的文献求助10
17秒前
Maglev完成签到,获得积分10
18秒前
18秒前
19秒前
烟花应助zxr采纳,获得10
19秒前
20秒前
20秒前
22秒前
夏小乖发布了新的文献求助10
23秒前
23秒前
24秒前
莫墨发布了新的文献求助10
24秒前
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7617262
求助须知:如何正确求助?哪些是违规求助? 9192513
关于积分的说明 19700362
捐赠科研通 7189573
什么是DOI,文献DOI怎么找? 3271994
关于科研通互助平台的介绍 2434749
邀请新用户注册赠送积分活动 2267043