Joel B. Montgomery

Two color missile signature measurements

Signature data was collected on surface-to-air and air-to-air missiles fired in August 1995. The data was collected using a staring 128/spl times/128 InSb sensor array with a two color filter wheel. This configuration allowed the collection of temporally correlated radiometrically calibrated mid-infrared images in two spectral bands at a colored frame rate of 100 Hz. Spectral bands were chosen to represent typical detection and discrimination bands in use for spectral discrimination in missile warning. Theoretical calculations using standard plume flowfield and radiative transfer models are compared with the measured data and conclusions are drawn as to model efficacy and relevancy.

Correlated two-color midinfrared background characteristics

Multicolor discrimination techniques provide a useful approach to suppressing background clutter and reducing false alarm rates in warning sensors. To assess discrimination performance, it is necessary to understand the statistics of each band as well as inter-band correlations. This paper describes the background measurements from an airborne platform collected using a two-color prototype staring missile- warning sensor. The sensor is a commercial 256x256 InSb camera with filter wheel integrated into a 90 deg by 90 deg. optic. The two colors lie in the carbon dioxide red spike region and in the window region below 4 micrometers. These bands are useful for detecting the combustion of hydrocarbons in the presence of background clutter. The sensor looks straight down from the aircraft and data is collected at frame rates from 10 to 100 Hz. Extensive background data has been collected over a wide range of scenes representing industrial, urban, rural, mountainous, and shoreline terrain. The data has been analyzed to provide correlated statistics of these spectral bands for both the underlying background structure and discrete false alarm sources. This data provides a basis for estimating the performance of spectral discrimination and optimizing processing algorithms for the suppression of clutter and rejection of false alarms.

Tactical mid-infrared background suppression in heavy clutter environments

Effective missile warning and countermeasures are an unfulfilled goal for the Air Force and DOD community. To make the expectations a reality, sensors exhibiting the required sensitivity, field of regard, and spatial resolution are needed. The largest concern is the first stage of a missile warning system, detection, in which all targets need to be detected with a high confidence and with very few false alarms. Typical sensors are limited in their detection capability by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm generators like burning fuels, flares, exploding ordinance, and industrial sources. Multicolor discrimination is one of the most effective ways of improving the performance of infrared missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in fielded scanning sensors. Utilization of the background and clutter spectral content, coupled with additional spatial and temporal filtering techniques have resulted in a robust real-time algorithm to increase signal-to-clutter ratios against point targets. Algorithm results against tactical data are summarized and compared in terms of computational cost as implemented on a real-time 1024 SIMD machine.

An advanced missile warning processing suite

Effective missile warning and countermeasures remain an unfulfilled goal for the Air Force and others in the DOD community. To make the expectations a reality, newer sensors exhibiting the required sensitivity, field of regard, and spatial resolution are being developed and transitioned. The largest concern is in the first stage of a missile warning system: detection, in which all targets need to be detected with a high confidence and with very few false alarms. Typical fielded sensors are limited in their detection capability by either lack of sensitivity or by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, arc welders, and industrial emitters. Multicolor discrimination has been shown as one of the effective ways to improve the performance of missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in multiple demonstration and fielded systems. New exploitations of background and clutter spectral contents, coupled with advanced spatial and temporal filtering techniques, have resulted in a need to have a new baseline algorithm on which future processing advances may be judged against. This paper describes the AFRL Suite IIIc algorithm chain and its performance against long-range dim targets in clutter.

Two color temporally correlated infrared background measurements

The use of high speed multicolor imaging sensors provides a valuable tool for characterizing both the signatures of missiles as well as clutter. Over 114 flight hours worth of collections were made of difficult to characterize clutter. This additional data can be utilized to develop and improve missile warning algorithms for better false alarm rates. These analyses show that although-a two color staring system could have multiple advantages over a single color system in false alarm rejection, the clutter rejection capabilities can be limited by the relatively low inter-band correlations between the red and blue bands.

A spectral independent morphological adaptive classifier

Effective missile warning and countermeasures continue to be an unfulfilled goal for the Air Force and DOD community. To make the expectations a reality, sensors exhibiting the required sensitivity, field of regard, and spatial resolution are being pursued. The largest concern is in the first stage of a missile warning system, detection, in which all targets need to be detected with a high confidence and with very few false alarms. Typical sensors are limited in their detection capability by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, and industrial emitters. Multicolor discrimination is one of the effective ways of improving the performance of missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in multiple fielded systems. Utilization of the background and clutter spectral content, coupled with additional spatial and temporal filtering techniques, have resulted in a robust adaptive real-time algorithm to increase signal-to-clutter ratios against point targets. The algorithm is outlined and results against tactical data are summarized and compared in terms of computational cost expected to be implemented on a real-time field-programmable gate array (FPGA) processor.

Tactical midinfrared testbed

A new tactical airborne multicolor missile warning testbed was developed and fielded as part of an Air Force Research Laboratory (AFRL) initiative focusing on clutter and missile signature measurements for algorithm development. Multicolor discrimination is one of the most effective ways of improving the performance of infrared missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in fielded scanning sensors. Normally, multicolor discrimination is performed in the mid-infrared, 3-5 micrometers band, where the molecular emission of CO and CO2 characteristic of a combustion process is readily distinguished from the continuum of a black body radiator. Current infrared warning sensor development is focused on staring mosaic detector arrays that provide much higher frame rates than scanning systems in a more compact and mechanically simpler package. This, in turn, has required that multicolor clutter data be collected for both analysis and algorithm development. The developed sensor test bed is a 256x256 InSb sensor with an optimized two color filter wheel integrated with the optics. The collection portion includes a ruggedized parallel array processor and fast disk array capable of real-time processing and collection of up to 350 full frames per second. This configuration allowed the collection and real- time processing of temporally correlated, radiometrically calibrated data in two spectral bands that was compared to background and target imagery taken previously. The current data collections were taken from a modified Piper light aircraft at medium and low altitudes of background, battlefield clutter, and shoulder-fired missile signatures during August 1999.

Mobile, embedded computer system for infrared data collection

The loss of aircraft to surface-to-air missiles in recent conflicts has focused renewed attention on building new infrared (IR) based missile warning systems. To ensure that these new systems are capable of discriminating missiles from background noise requires a thorough characterization of both the background noise and the missile signature data in the infrared spectrum. The best method for collecting these data is through the use of airborne IR imaging systems and their corresponding data collection units. Unfortunately, the physical size, power consumption, weight and cooling requirements of current data collection units prevent them from being used in most airborne applications. One goal of the Avionics Laboratory is to collect IR data for background characterization studies. Decreasing research budgets dictate that these data be collected economically. Therefore, Avionics Laboratory in-house personnel designed, built and fielded a low-cost IR data collection system mounted in a light aircraft. The design of the data collection system and some examples of imagery collected by the system are presented.

Advancement and results in hostile fire indication using potassium line missile warning sensors

M&M Aviation has been developing and conducting Hostile Fire Indication (HFI) tests using potassium line emission sensors for the Air Force Visible Missile Warning System (VMWS) to advance both algorithm and sensor technologies for UAV and other airborne systems for self protection and intelligence purposes. Work began in 2008 as an outgrowth of detecting and classifying false alarm sources for the VMWS using the same K-line spectral discrimination region but soon became a focus of research due to the high interest in both machine-gun fire and sniper geo-location via airborne systems. Several initial tests were accomplished in 2009 using small and medium caliber weapons including rifles. Based on these results, the Air Force Research Laboratory (AFRL) funded the Falcon Sentinel program in 2010 to provide for additional development of both the sensor concept, algorithm suite changes and verification of basic phenomenology including variance based on ammunition type for given weapons platform. Results from testing over the past 3 years have showed that the system would be able to detect and declare a sniper rifle at upwards of 3km, medium machine gun at 5km, and explosive events like hand-grenades at greater than 5km. This paper will outline the development of the sensor systems, algorithms used for detection and classification, and test results from VMWS prototypes as well as outline algorithms used for the VMWS. The Falcon Sentinel Program will be outlined and results shown. Finally, the paper will show the future work for ATD and transition efforts after the Falcon Sentinel program completed.

Performance of SIMAC algorithm suite for tactical missile warning

Self protection of airborne assets has been important to the Air Force and DoD community for many years. The greatest threats to aircraft continue to be man portable air defense missiles and ground fire. AFRL has been pursuing a near-IR sensor approach that has shown to have better performance than midwave IR systems with much lower costs. SIMAC couples multiple spatial and temporal filtering techniques to provide the needed clutter suppression in the NIR missile warning systems. Results from flight tests will be discussed .