This brief narrative was written to explain to the interested reader salient features of the SSI development methodology.
Proven Experience in the Defense Arena
One of SSI's greatest strengths is the ability of its personnel to evaluate sensor technologies within the context of their intended applications. Much of SSI's experience in this area is related to defense systems, such as warning receiver evaluation, FTIR spectrometry, and standoff collection systems development. Our ability to work in such a diverse range of applications is founded on a consistent system development methodology that is not specific to any particular discipline.
Transitioning to Commercial Applications
This methodology is equally applicable to many commercial needs, such as developing solutions for quality assurance, automated inspection, surveillance, and pollution monitoring, just to name a few. In approaching a new problem, we use a balanced combination of system performance simulation, laboratory testing and field testing. Too often, organizations use laboratory results alone to base technology investment decisions without properly evaluating the required specifications or performance expectations in the actual measurement environment.
Role of Simulation and Testing
The SSI methodology begins with a thorough understanding of the quantities being measured and how external forces affect them. This is because an understanding of the sensor technologies alone is usually insufficient to solve most remote sensing problems. SSI uses simulations of the measurement scenario to predict the "observables" for the customer's problem. These simulations are then possibly followed up by measurements to validate the predictions and identify potential problems with the measurement approach being considered.
These effects can all be modeled reliably to estimate what a particular object looks like in the sensor's "eyes". The observables must include background effects such as ground and atmospheric emission and scattering as well as clutter sources. Often, the ability of the receiver to accurately measure the signal from the source is not only a function of sensitivity of the optical receiver, but also of the ability of the receiver to discriminate between the desired signal and other types of clutter that may potentially interfere with the source signal. Through a combination of simulation and testing, a reasonable picture can be developed for how a system will perform in a given scenario.
The SSI methodology considers the customer's problem from end to end. Thus, beyond the receiver design, it is also important to consider the ultimate data product that will be produced. For example, a system involving image acquisition hardware, such as an assembly line inspection system, might require high speed image processing to determine whether the product meets the company standard for quality. In this case, the data product is not the raw data (i.e., the image itself), but rather a quantity that directly reveals whether each sample meets the standard (e.g., quantitative measures of product standards such as size, color, weight, etc.). Furthermore, the solution requires not only image processing hardware, but also algorithms customized for the particular application. SSI has used simulations of observables to serve as inputs to automated processing algorithms that can be tested before hardware is operational. This approach greatly reduces the risk in developing expensive new hardware.
Addressing Unique Requirements
Many remote sensing problems cannot be solved with commercial off-the-shelf (COTS) hardware. One of SSI's greatest strengths is in developing innovative system approaches to challenging measurement problems. Determining the best approach for a given measurement application requires a disciplined and quantitative evaluation approach, and SSI can support this process in several different ways:
- In the feasibility study and/or design phases, SSI performs technical evaluations of candidate system architectures to quantitatively assess the utility of the solution within the context of the environment in which it will be used. In many cases, all of the factors that impact system performance are well understood.
- When uncertainties in the observables or technologies exist, the level of risk in moving directly to a full-scale prototype is increased. SSI can propose and conduct focused experiments to resolve such issues that cannot be resolved by other means.
- Once a successful prototype solution is demonstrated, SSI and its affiliated consultants/partners can provide direct support to our customers in developing final product hardware and data processing algorithms.
SSI's approach to solving customer's problems is summarized by our "Formula for Success." The level of SSI involvement in a customer's effort can vary from simply helping define system requirements all the way to actually building instrumentation and implementing data processing algorithms. The formula is summarized by the following steps:
- Listen
- Assist in developing requirements
- Analyze candidate solutions
- Recommend strategic plan
- Implement customer-selected solution
The most critical part of the problem-solving process is understanding the needs of the customer. In many cases, the need for a solution is apparent, even though the specific requirements are not. Rather than pushing particular technologies at problems, SSI first listens to customer needs and concerns.
SSI can assist customers in developing technical specifications and requirements by leveraging our experience with applicable technologies.
Solution feasibility is evaluated by using analytic tools to simulate the application and the quantities being measured. In some cases, developing hardware prototypes is part of this process. The optimal solution will need to strike a balance between providing the necessary technical performance as well as meeting cost and schedule constraints. In addition, the optimal solution may require provisions for future capability expansion.
SSI provides the customer with a practical, concise plan with steps for implementing the solution.
By leveraging expertise in system development, measurement execution, and algorithm design, SSI can support the implementation process in two ways. SSI can implement the analytic, experimental, or hardware solutions directly by utilizing a combination of in-house capabilities and affiliated partners. Alternatively, SSI provides management consulting services to assist the customer in solution development.
In summary, the SSI approach provides a tremendous advantage to the project manager faced with a challenging set of requirements. Our technical consulting services allow performance, cost, and schedule issues to be evaluated as a set, which allows potential risk items to be identified early on in the development phase. In addition, this comprehensive approach insures that top-level requirements are accurately propagated among the various organizations involved in the project. This in turn leads to more effective designs with clearly identified requirements, thus streamlining the overall development process.
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