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Toward a Better Definition

1. It would be easy to seek out a cute slogan or catchphrase to define MASINT:

MASINT is the “C.S.I.” of the intelligence community.

This definition does allude to the detailed scientific analysis behind much of MASINT and might be okay for the ‘farmer in the field’, but it is inadequate and inappropriate for real use. [Note that the ‘farmer’ using hyperspectral sensing, GIS databases, and chemical analysis to put down the exact amount of fertilizer in his field – a new practice called “precision farming” – would likely understand and appreciate many MASINT applications]

2. It might be possible to describe MASINT in context of another scientific discipline:

MASINT is like Astronomy except for the direction of view.

Astronomers use remote sensing, also across much of the electromagnetic spectrum, to discern the universe. They use certain wavelengths to peer through dust and gas surrounding objects of interest. They use other wavelengths to determine the composition of matter in a particular scene. They use still other wavelengths to try to understand things they theorize to be true but can’t directly measure. In the end, they produce “false color” pictures from the 1s and 0s pouring out of their instruments. These images give them, and the rest of us, the context for what they observe. But the underlying data – whether spectral wavelength, radiometric data, or energy intensity – are the keys to understanding the phenomena they see.


Crab Nebula Wavelengths

Credit: NASA/Marshall Space Flight Center

As a final comparison, just like MASINT, Astronomy now has its materials sub-discipline. Astronomers have sent probes to gather particles from the solar wind and comets and will soon send probes to Mars for sample–return missions. However, while MASINT can be compared to a scientific discipline like astronomy, it is probably not the best way to characterize an intelligence discipline.

3. So, how about defining MASINT by its component parts?:

MASINT is best described by its six sub-disciplines: Radar, RF, Geophysical, Nuclear Radiation, Materials and Electro-Optical

MASINT has often been characterized by its six sub-disciplines shown in the illustration below. These sub-disciplines are carryovers from the consolidation of diverse activities into MASINT and are useful to technologists and phenomonologists who have to match sensing technologies to observable phenomena associated with a particular target or activity.

These sub-disciplines might be useful to the technologists and phenomonologists, but they are problematic for the rest of us. That’s because everything else we organize MASINT by in the real world (budget, systems, operations, TPED) doesn’t neatly fit with these six sub-disciplines. If we look at a particular sub-discipline, electro-optical

MASINT Diciplines

(EO) for example, we find a range of systems from handheld to space-based; active and passive; funded, operated and maintained by several different organizations; exploiting different phenomenologies, using different algorithms for different objectives. From this it should be recognized that it is impossible to manage EO – or any MASINT sub-discipline – as a distinct business line of MASINT. Therefore, this is probably not the best way to define MASINT either.

4. Rather it might be better to describe MASINT as a collection of capabilities:

MASINT is loose collection of several Family-of-System (FoS) capabilities having the common objective of discerning an adversary’s capabilities and actions through collection and exploitation of metric and signature information.

Now we divide MASINT into understandable, functional portfolios. In doing so, we use the following criteria: a MASINT FoS or portfolio should encompass a set of capabilities, dedicated or otherwise, which have more than one of the following in common:

  • Predominantly respond to a specific set of intelligence needs or requirements
  • Predominantly funded in one budget aggregation (or one for acquisition and a separate one for operation and sustainment)
  • Predominantly operated and sustained by one organization or echelon (or one for the sensors and one for the operations)
  • Predominantly supports one major mission area (or supports all mission areas indiscriminately)
  • Predominantly uses the same tasking, processing, exploitation and dissemination (TPED) chain
  • Predominantly handled in the same classification arena
  • Predominantly falling within one sub-discipline

There are several advantages to defining MASINT as a set of FoS’s vice the six sub-disciplines:

  • MASINT practitioners typically are knowledgeable across the range of capabilities within a particular FoS
  • MASINT consumers are typically most interested in a set of products from a particular FoS – irrespective of the sub-discipline
  • Planners and programmers responsible for investment decisions have an easier time understanding the capabilities and limitations of a particular FoS and should therefore make more-informed decisions
  • It is much easier to develop useful architectures, roadmaps, operational concepts and policies for an individual FoS than it is for a MASINT sub-discipline.

By way of example, two potential MASINT FoS capabilities are Imagery-Derived MASINT (IDM) and close-in MASINT.

IDM takes output of conventional imagery systems and processes the data in a different way to extract the non-literal information content. For example, rather than producing a multi-colored literal image from a multi-spectral sensor, a MASINT processing and exploitation application would try to discern the precise materials in the field of view through spectral matching. Each pixel in the field of view is a data set – corresponding to a particular material or set of materials. The real power comes when the MASINT signature information is referenced spatially in the image providing both content and context to the analyst. Referenced to a precise geographic registration system this integrated product provides information-rich intelligence to the consumer.

Close-in MASINT refers to sensors that are emplaced in close proximity to a target with the purpose of gathering signature information to discern activity of interest. These sensors may fall into any one of the six sub-discipline or be multi-discipline. The sophistication, longevity, and mode of employment varies by application. The key to close-in MASINT is the signatures. DIA’s National Signature Program initiative is essential to catalog, assess, and make available the signatures necessary to do the close-in MASINT mission as well as provide the same signatures to weapon system developers.

The factors that make these good candidates for MASINT FoS is evident. Examining the remainder of the MASINT capability-universe would yield a total of 6-8 FoS’s. Defining MASINT by these FoS portfolios would create significant understanding of the “business” of MASINT. Organizing and managing MASINT by these 6-8 portfolios would be logical, simplifying, and productive. One drawback – the list of reasonable MASINT FoS’s is probably classified.

Perhaps we need to examine the past to come up with a definition for the future.

<---Defining MASINT

Historical Context--->

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