Airborne EO imagery, including wideband, hyperspectral, and multispectral modalities, has greatly enhanced the ability
of the ISR community to detect and classify various targets of interest from long standoff distances and with large area
coverage rates. The surf zone is a dynamic environment that presents physical and operational challenges to effective
remote sensing with optical systems. In response to these challenges, BAE Systems has developed the Tactical Multi-spectral
(TACMSI) system. The system includes a VNIR six-band multispectral sensor and all other hardware that is
used to acquire, store and process imagery, navigation, and supporting metadata on the airborne platform. In
conjunction with the hardware, BAE Systems has innovative data processing methods that exploit the inherent
capabilities of multi-look framing imagery to essentially remove the overlying clutter or obscuration to enable EO
visualization of the objects of interest.
KEYWORDS: Signal to noise ratio, Computing systems, Target detection, Long wavelength infrared, Data modeling, Systems modeling, Infrared imaging, Imaging systems, Electro optical systems, Sensors
Electro-optical (EO) systems with digital image processing and computer-aided detection are increasingly coming into use for maritime surveillance, reconnaissance and search and rescue. EO systems have the potential to improve the consistency of detection, reduce operator workload and fatigue, and improve search efficiency. However, quantifying their performance versus more traditional approaches is problematic, because of the differences in how performance is specified for traditional systems versus modern computer-aided designs. In maritime search applications, system performance is commonly specified in terms of the lateral range curve (LRC). The LRC is a plot of the probability of detection versus horizontal range from the search platform. This metric has a long history, rooted in visual searches by trained human observers. However, it is specified without reference to any false-alarm rate or probability of false alarm. Computer-aided EO performance, on the other hand, is usually specified in terms of Signal-to-Noise Ratio (SNR), Receiver Operating Characteristic (ROC) curve, or some equivalent metric. In this paper, we demonstrate a methodology for estimating LRCs from SNRs or ROC curves. This methodology provides a consistent, quantifiable means for comparing the performance of new and legacy systems.
This investigation centered on the most challenging search and rescue requirements: finding small targets in high seas. Our course of action was to investigate the capabilities of known hyperspectral and LWIR sensors in realistic conditions of target and environment to drive the design of a sensor system capable of substantially improving search efficiency and efficacy for these conditions. The relevant results from this study include demonstration of significant power in clutter rejection (e.g., whitewater and wave complexity) by the LWIR sensor. In addition, several factors combine to indicate that a modest implementation of HSI and IR sensors would provide significant improvement in search efficiency and efficacy for small targets in high seas. These factors include high PD, low PFA, and the untiring nature of the sensors when combined with the potential of real-time automatic target/background discrimination. This modest implementation would translate directly into faster, more complete coverage, at lower overall costs to the USCG, and a more likely probability of a successful search mission.
Science and Technology International (STI) has developed a six-band multispectral imager optimized for surf-zone reconnaissance and mine countermeasures (MCM). Airborne surf-zone MCM requires both accurate spectral imaging and high spatial resolution. Vibration and aircraft motion degrade the image quality. However weight, volume and power constraints preclude stabilized operation of the cameras. Thus, the MTF needs to be measured in flight to insure it meets the resolution requirements. We apply the slanted-edge MTF method to the in-flight characterization of airborne high-resolution cameras, analyzing images of orthogonal slanted edges to estimate the motion and vibration contributions to the MTF, and show that the system exceeds the resolution requirements for surf-zone MCM. We also develop a methodology for scaling to other altitudes and speeds, and show that the system will perform well throughout its operational envelope. The slanted-edge method is more accurate and reproducible than the alternative of placing MTF bar targets under the aircraft flight path. Further, the slanted-edge targets are easier to deploy and recover, and ease the navigation tolerances.
The shallow water and surf zone (SZ) regions are one of the more difficult environments currently being addressed in littoral mine counter measure (MCM) strategies, yet they are also critical regions for MCM with respect to military breaching tactics. The difficulties in optical remote sensing of the SZ lie mostly in the problem of clutter, which includes transient wave glint, foam patches, turbidity, and detritus. The problem is compounded by the refractive distortion of the small targets (mines and barriers) in these shallow waters. We have adopted several strategies for dealing with clutter rejection in the SZ. The first is a strictly statistical approach to clutter rejection, which is computationally efficient and mathematically simple. The second of these leverages hyperspectral algorithms used for the detection of submerged targets in deep water, wherein the glint is subtracted from the scene prior to image segmentation and anomaly detection. The second method, while more mathematically mature, does not appreciably increase the computation time and provides startlingly better results.
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