FACILITATING INFRARED SEEKER PERFORMANCE TRADE STUDIES USING DESIGN SHEET

Transcription

1 FACILITATING INFRARED SEEKER PERFORMANCE TRADE STUDIES USING DESIGN SHEET Sudhakar Y. Reddy and Kenneth W. Fertig Rockwell Science Center, Palo Alto Laboratory Palo Alto, California and Anne Hemingway Rockwell International, Tactical Systems Division Duluth, Georgia September 25, 1995 The work reported in this document is supported by the Advanced Research Projects Agency of the Department of Defense through Wright Patterson Air Force Base under contract F C-4426.

2 Table of Contents 1. INTRODUCTION DEVELOPING THE INFRARED SEEKER PERFORMANCE MODEL THERMAL IMAGING SYSTEMS PERFORMANCE MODEL FLIR BASIC CHARACTERISTICS OF THE DESIGN SHEET MODEL USING DESIGN SHEET MODEL FOR TRADE STUDIES CURRENT STATUS AND FUTURE REQUIREMENTS REFERENCES I

3 1. INTRODUCTION The Tactical Systems Division of Rockwell International is a supplier of infrared (IR) seeker based weapons systems. An important part of their activities is the design of missile seeker systems. During the conceptual design phase of these systems, an engineering concept team makes decisions which will ultimately affect the quality, cost, performance, availability and reliability of the weapon. Realizing the importance of the conceptual design phase, TSD has initiated efforts to popularize the use of computer-based analytical tools during the early phases of design. FLIR92 [1], a computer model developed by the US Army Night Vision Laboratory, is currently used for system level design analysis of infrared seeker systems. In spite of its accuracy and utility, it is limited by a lack of flexibility. This model can only perform an analysis of a single design at a time. Though one could modify it to perform analysis of several designs at a time in a batch mode of operation, the lack of integrated trade-study capability does not lend the FLIR92 model for easily searching large areas of design space before making crucial design decisions. The Palo Alto Laboratory of the Rockwell International Science Center has a strong research program in conceptual design methodology. The centerpiece of this program is the Rockwell-proprietary software system called Design Sheet. Design Sheet is a flexible analysis tool for carrying out engineering trade studies. Design Sheet uses algebraic equations for modeling, and integrates robust equation solving routines with graphical trade study capabilities to provide a powerful tool for quickly searching vast design spaces. Design Sheet only needs the design equations in a declarative mathematical form, without requiring the user to provide any control information on how the equations are solved. The user can decide at run-time, which variables are input and which are the desired output, and the internal graph-theoretic algorithms figure out a robust way for solving these equations. Therefore, the user can decide at run-time what trade studies are desired to search the design space and Design Sheet performs these trades without requiring any additional coding effort on the part of the user. An important goal of this project and the primary subject of this report is the development of a Design Sheet model of infrared seeker performance. The next section documents the model development process and describes the various components of the model. It then demonstrates how the Design Sheet model can be used for performing interesting design trade studies. Finally, this report concludes with a discussion of the current status and the future plans in developing and using Design Sheet based models for designing infrared seekers. 1

4 2. DEVELOPING THE INFRARED SEEKER PERFORMANCE MODEL The Infrared Seeker Performance Model seeks to integrate criteria from optical, mechanical and operational aspects of seeker design into a single model, so that performance trades from multiple perspectives can be effectively used during seeker design. Design Sheet is used as a modeling platform, because of its strengths in integrating models from different perspectives into a single environment and its built-in capabilities for carrying out trade studies. The development of the seeker performance model is expected to be an evolutionary process. Initially, a core model for predicting the IR imaging system performance measure of minimum resolvable temperature difference will be developed based on the FLIR92 [1] model. Then, individual submodules pertaining to other aspects of infrared system design will be developed and incrementally added to the core model. Figure 1 shows the proposed modular architecture of the integrated seeker performance model. The seeker model includes scenario specific (atmospheric, terrain, target, etc.) as well as design specific (optics, electronics, sensor, software, display, etc.) information. Atmospheric Effects Mechanical Structural Mechanical Envelope Background Model Software Cost FLIR 92 (core analysis) Tracker Optics Electronics Target Signature Mechanical Thermal Detector (First Principles) Figure 1: Proposed integrated seeker performance model The modular incremental development is facilitated by Design Sheet. Among the many advantages of such an approach are the ease of debugging and testing during model development and the ability to replace individual modules when specific technologies change. An important advantage of using Design Sheet for developing the model is that the developed model can be used for any arbitrary trade study. In contrast, most current models are developed for specific predefined trade studies. The rest of this section describes the FLIR92 model which is the basis for the core analysis module. This is followed by a brief description of the basic 2

5 characteristics of the Design Sheet model, and the extensions to it for predicting the probability of detection. 2.1 Thermal imaging systems performance model FLIR92 FLIR92 [1], a computer model developed by US Army Night Vision and Electronic Sensors Directorate to predict performance of IR imaging systems, forms the core of the seeker performance model being developed in this project. FLIR92 is a system evaluation tool that uses basic sensor parameters to predict overall system performance for comparison to a set of performance requirements necessary to meet a target acquisition and discrimination task. The impact of basic sensor and sensor component designs on overall system performance can be evaluated to arrive at an optimal system configuration for the specified task. This model uses basic system-level design and operational parameters to calculate three widely accepted system performance measures, namely the modulation transfer function (MTF), the minimum resolvable temperature difference (MRTD), and the minimum detectable temperature difference (MDTD). Illustrated in Figure 2 are the major system components used in the model. Radiation from the target and the background scene is captured by the seeker optics. The photons are passed through the lens and focused onto a sensor which converts the energy into an electric signal. The system electronics process the signal from the detector into a format which is suitable for re-display to a human observer. The observer then makes a decision as to whether the viewed target is discernible based on the displayed information. Target Optics FPA Electronics Processing Display Observer Figure 2: Thermal imager block diagram The model consists of equations which reflect how the signal is modulated from the target to the observer. The model calculates the total system transfer function using the linear filter theory, by calculating MTFs for individual system components and then multiplying them together. The model calculates MTFs due to system components such as optics and electronics, sensor design characteristics and operational environment. The observer is also modeled as a system component for the purpose of calculating the MTF. The component MTFs are divided into three groups: prefilters, postfilters, and noise filters, and the product of prefilter and postfilter MTFs yield the total system MTF. A further distinction is made between the temporal and spatial postfilter MTFs, because the model handles both scanning and staring systems. MRTD and MDTD are used as infrared system performance measures. The MRTD is the minimum temperature difference between a standard bar target (four 3

6 7:1 aspect ratio bars) and the background that is required in order for a standard observer to just fully resolve the target. MRTD is defined for the horizontal and vertical directions, depending on the target pattern orientation. MRTD depends on the system transfer function (resolution) and the system sensitivity. To predict MRTD and MDTD, the spatial integration of the eye/brain system is modeled. The MDTD is the minimum temperature difference between a square target and the background required to make the target detectable to a standard observer. MRTD is the best overall indicator of thermal imager performance. MDTD is less stringent a performance measure, but can include the detection of objects that are smaller than a single pixel dimension. It is important to note that to identify and distinguish between battlefield targets, MRTD is a more appropriate measure of system performance. The model also has equations for the effects of various noise parameters on the overall system performance (MRTD and MDTD). As described in [1], system noise is modeled in the MRTD predictions by developing a scaling factor that multiplies the random spatio-temporal noise by the amount of excess system noise. System noise is reduced to components that add in quadrature, with the appropriate eye spatial and temporal integration effects considered in each noise component. The noise analysis methodology isolates system noise into eight components. 2.2 Basic characteristics of the Design Sheet model A Design Sheet model to duplicate the major aspects of the FLIR92 model has been completed. As explained earlier, the purpose of this effort is to allow for easy extensibility of the model, and more importantly to be able to perform novel trade studies which require the model to be inverted with ease to calculate design parameters based on performance requirements. Currently, the Design Sheet model has 17 component MTFs and eight noise components, represented by 124 scalar variables, 72 constraints and 69 transforms. They model both the staring and scanning type of IR imagers, which operate in the mid-wave to long-wave infrared spectral bands. In addition to the equations for MRTD and MDTD, the Design Sheet model has equations for predicting the probability of detection of a target based on system MRTD and target size and range. It is this ability of Design Sheet to easily integrate additional model fragments that contribute to the flexibility of the resulting seeker design system. Design Sheet uses a graphical representation to depict equations and variables in the model. Figure 3 shows the constraint network of the seeker performance model. The square nodes depict relations and the hexagonal boxes represent variables. An arc between a variable and a relation denotes that the relation involves the variable. The direction of the arc denotes the computational sequence. An outgoing arc from a relation to a variable denotes that the relation is being used to calculate the variable. One should note that a relation can only used to calculate one variable. 4

7 Figure 3: Seeker performance model constraint network Figure 3 is only shown here to impress upon the reader the size of the actual network. Figure 4 shows a simplified constraint network., showing only the part of the network that is of the most use in performing the trade studies described in this report. The variables of importance are the design parameters, focal length and ratio of focal length to diameter of optics (f#), the performance parameters, field of view (FOV), probability of detection (POD), minimum resolvable temperature difference (MRTD), and the operational characteristics, target range and spatial frequency. 5

8 Figure 4: Abstract version of the constraint network The arrows in Figure 4 denote the natural flow of data in the constraint network. This is the mode in which the original FLIR92 model is used. In this mode, given the design and operational parameters, the model calculates the performance metrics. Test cases have been run in this mode to verify that the results produced by the Design Sheet model are accurate with reference to the original FLIR92 model. In order to calculate the performance metrics, the user interacts with the model through a top-level graphical user interface shown in Figure 5. There are four panes, the right hand side is the variable pane, and the left hand side is divided into the command pane, the display pane and the relation pane, respectively from top to bottom. The variable pane serves as a spread sheet, and when new values of input/independent variables are entered, they are propagated. The top menu line of the interface can be used to access various commands, the most interesting of which are the commands for defining trade studies between variables and generating plots of the ensuing results. These commands can be accessed from the Analysis menu. The other menus enable the user to define and modify variables and relations, and to load and save models. 6

9 Figure 5: Design Sheet user interface In addition to calculating the MRTD of a specific seeker design, the seeker performance model can also be used in the traditional forward mode to calculate the various modulation transfer functions (MTFs). Figure 6 shows the plots of both the total system MTF and some of the important component MTFs as a function of spatial frequency. Producing this graph requires only minimal effort, as the plotting capability is integral within Design Sheet. All that is required of the user is to type in the x-axis and y-axis variable names, and the ranges for the x-axis variable. The ability to study the performance characteristics of a specific seeker design is an important capability in itself. However, the uniqueness of Design Sheet is in being able to use this model for performing trade studies over large tracts of design space, before selecting a specific design. Especially interesting and extremely useful are the trades that involve fixing some of the performance requirements (e.g., the range vs. field of view trade for a specified probability of detection). Some interesting trade studies are reported in the next section. 7

10 M Detector Temporal M FPA integration M geometric blur M random image motion M total system M diffraction M detector spatialm crt M display sample&hold Figure 6: Total system MTF and some component MTFs 3. USING DESIGN SHEET MODEL FOR TRADE STUDIES As stated earlier, the power of Design Sheet lies in the ability to perform trade studies easily. Such studies allow the designer to search vast areas of design space quickly before making design decisions. This section will show some of the trade studies that were performed using the Design Sheet model of seeker performance. Though the model itself has equations for both the scanning as well as the straring systems, the trade studies shown here are only for the scanning system. One of the characteristics that is often considered by seeker designers is the tradeoff between MRTD (horizontal) and spatial frequency (fspat). A good seeker design should not only have smaller values of MRTD, but the variation of MRTD with fspat should be small for spatial frequencies of interest. In order to verify the effect of different optics designs on the MRTD vs. fspat characteristics, the designer can generate a plot of this characteristics for different optics designs (focal length = 250 mm with varying f#). Such a plot can be generated quickly and easily in Design Sheet, and is shown in Figure 7 for the horizontal direction. A comparison of the horizontal and vertical MRTDs can be obtained as well, and is shown in Figure 8. As stated earlier, these trades are for a scanning system. Similar trades could easily be obtained for a staring system. 8

11 Figure 7: The effect of optics design on MRTD vs. fspat characteristic Figure 8: Horizontal and vertical MRTD for a scanning system 9

12 In addition to the traditional plots for evaluating a specific seeker design, Design Sheet can be used to search a large design space by performing non-traditional trades. For example, MRTD is traditionally an output of the seeker performance model, where as fspat is the input. In Design Sheet, however, the state of these two variables can be switched. The new state of the directed constraint graph is shown in Figure 9. This can be done easily and only requires a couple of mouse clicks; first the variable fspat is made undetermined and then the variable MRTD is made independent. The computational plan for the new state of the model is automatically determined by Design Sheet. In this case, the computational plan requires a system of equations involving MRTD and fspat need to be simultaneously solved. The model in this state can be used to specify a fixed value of MRTD and a tradeoff between probability of detection and target range obtained. Figure 10 is a plot of probability of detection vs range for MRTD of 0.1 and lens focal length of 250 mm. The effect of f# is also depicted on the plot, by repeating the plot for two different values of f#. In similar vein, the probability of detection could be made input instead of MRTD, and a tradeoff plot obtained between the MRTD (or resolvable temperature difference) and target range. Such a plot for two different probabilities of detection is shown in Figure 11. f# Focal Len. Fspat Range POD FOV MRTD Figure 9: Constraint graph with MRTD as input 10

13 Figure 10: Tradeoff between target range and probability of detection Figure 11: MRTD vs. target range tradeoff for a fixed probability of detection 11

14 Finally, let us consider an even more interesting trade study. A designer is often provided with requirements on the minimum temperature differences that need to be resolved (MRTD) as well as the probability of detection (POD) that is desired. Under these circumstances,, there is a tradeoff between the target range and field of view given a specific MRTD and POD. Knowing this tradeoff would enable the conceptual designer to provide a more appropriate specification on the target range in the requirements specification stage. Figure 12 shows the directed constraint graph for this state of the model. The data flow in the model from focal length, f#, MRTD and POD to field of view (FOV) and target range is in a direction that is reverse of the data flow in the traditional use of the model. It is this ability to reverse the flow directions that makes Design Sheet a powerful tool for performing trade studies in support of conceptual design. f# Focal Len. Fspat Range POD FOV MRTD Figure 12: Constraint graph with both MRTD and POD being independent Figure 13 shows the tradeoff plot between filed of view (in the vertical direction) and target range for specified values of 0.1 for MRTD (in the vertical direction) and 0.7 for probability of detection. This plot is called a cross plot and plots two dependent variables on the x and y axes. The independent variables that are 12

15 varied are the focal length and f#, and the different values of these variables are shown on the plot. FocalLength=100 f#=2 f#=3 f#=4 FOV (mr) FocalLength=200 FocalLength=300 Figure 13: Tradeoff between field of view and target range Based on the trade-off shown in Figure 13, and other relevant information about the operational regimes for field of view (FOV) and target range, the designer can choose appropriate values for focal length and f/#. The trade studies shown in this section are only examples and are by no means the only ones used by designers in developing infrared seekers. 4. CURRENT STATUS AND FUTURE REQUIREMENTS This project clearly demonstrates not only that complex models can be implemented using Design Sheet but also the ease with which trade studies can be performed. It cannot be over emphasized that many of the above trade studies are possible because the MRTD and POD models could be merged together easily, in addition to being able to reverse the data flow across the model easily at run time. The strength of Design Sheet lies in its ability to let the designer do these tasks naturally and easily. Trade studies shown here have been obtained in a matter of minutes, where as they could have taken hours if not days to produce using traditional means. Currently, only the core analysis model is available in Design Sheet. In future, we plan to integrate mechanical, thermal aspects of the performance model. We also plan to integrate a cost model to perform cost-performance tradeoffs. In a related 13

16 effort, Design Sheet is also being integrated with a solid modeler (IDEAS). A parametric geometric model of the conceptual seeker design will be linked with the Design Sheet based performance model for carrying out more interesting and useful trade studies. 5. REFERENCES [1] FLIR92 Thermal Imaging Systems Performance Model, U.S. Army Night Vision and Electronic Sensors Directorate, Ft. Belvoir (Virginia), Document , January