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Radar Surface Clutter Simulation

Surface clutter consists of radar reflections that emanate from terrain, vegetation, man-made structures, and ocean waves. Incorporate surface clutter into your Radar Toolbox simulations to determine if monostatic narrowband radar systems can distinguish between clutter and targets of interest. Topics covered include:

Overview of Surface Clutter Capabilities

This table provides an overview of surface clutter modeling capabilities in Radar Toolbox organized by power-level, measurement-level, and waveform-level applications. The highest-fidelity simulations model dynamic scenarios with moving targets and support site-specific, geolocated terrain models and atmospheric refraction on a curved Earth.

FidelityUsageRadar Toolbox FunctionalityOutputComputational ComplexityDynamic ScenarioSite-SpecificCurved Earth

Power-Level Simulation

System-level analysis, range onlyclutterSurfaceRCSClutter patch RCS as a function of rangeLow

System-level analysis, range and DopplerclutterSurfaceRangeDopplerRCSClutter patch RCS as a function of range and DopplerLow

Interactive system-level analysisRadar Designer app

Export plots, metrics, and MATLAB® scripts

Low

Measurement-Level Simulation

Algorithm design

Tracker design and tuning

radarDataGenerator in a radarScenario with clutterGenerator enabled

Detections

Track reports

Medium

Waveform-Level Simulation

AI training

Algorithm design

constantGammaClutter and gpuConstantGammaClutterI/Q signals of clutterMedium

End-to-end analysis in range and Doppler

Algorithm design

radarTransceiver in a radarScenario with clutterGenerator enabled and ScattererDistribution set to "RangeDopplerCells"

I/Q signals of scenario, including targets in clutterMedium

High fidelity, end-to-end analysis

Algorithm design

radarTransceiver in a radarScenario with clutterGenerator enabled and ScattererDistribution set to "Uniform"I/Q signals of scenario, including targets in clutterHigh

Power-Level Simulation

Power-level simulations of radar systems account for transmitted and received power and are used for system-level design. You can perform link budget analysis to predict performance metrics like detection range and signal-to-noise ratio using the Radar Designer app. Power-level applications that incorporate clutter are based on clutter patch Radar Cross Section (RCS) calculations and include:

  • Clutter-to-noise ratio (CNR) as a function of range

  • CNR as a function of range and Doppler

  • Target detectability studies

This tables provides information on power-level surface clutter models, capabilities, and simulation approaches available in Radar Toolbox, organized by application.

ApplicationHow to Model Using Radar ToolboxExamplesAdditional Information

Calculate clutter patch Radar Cross Section (RCS) to determine:

  • Clutter-to-noise ratio

clutterSurfaceRCS outputs RCS as a function of range for clutter patches characterized by NRCS.

clutterSurfaceRCS supports:

Use the RCS of a clutter patch as an input into radareqsnr to calculate the clutter-to-noise ratio.

Return the Normalized Radar Cross Section (NRCS) for built-in surface models using:

Analyze surface clutter presentation in range-Doppler space for:

  • Target detectability studies

  • Receiver saturation

  • Clutter-to-noise ratio

clutterSurfaceRangeDopplerRCS outputs RCS as a function of range and Doppler for clutter patches characterized by NRCS.

clutterSurfaceRangeDopplerRCS supports:

  • Arbitrary accuracy of numerical integration

  • Doppler wrapping

Use the RCS of a clutter patch as an input into radareqsnr to calculate CNR.

Return the Normalized Radar Cross Section (NRCS) for built-in surface models using:

Assess system performance of clutter-limited systems for:

  • Target detectability studies

  • Clutter-to-noise ratio as a function of range

Radar Designer app performs interactive system-level analysis that includes the clutter-to-noise ratio as a function of range (CNR vs Range) plot.

Radar Designer app supports:

  • Built-in land and sea surface models

  • Atmospheric refraction and attenuation

Use Radar Designer to:

  • Calculate performance metrics

  • Visualize range/Doppler coverage

  • Export design sessions to MATLAB scripts

Measurement-Level Simulation

Measurement-level simulations of radar systems account for signal processing chain gains and losses, measurement uncertainty, and environmental effects to provide probabilistic target detections. You can use the statistical radar model, radarDataGenerator, as part of a radar scenario to assess performance metrics such as probability of detection in the presence of noise and false alarms. Measurement-level applications that incorporate clutter include:

  • Target detectability studies

  • Tracker tuning

  • Clustering analysis

This tables provides information on measurement-level surface clutter models, capabilities, and simulation approaches available in Radar Toolbox.

ApplicationHow to Model Using Radar ToolboxExamplesAdditional Information

Generate probabilistic detections of targets in clutter within a dynamic scenario that includes processing chain gains and losses for:

  • Target detectability studies

  • Tracker tuning

  • Clustering analysis

Use radarDataGenerator as part of a radarScenario with clutterGenerator enabled to model target detections in clutter.

radarDataGenerator generates raw detections and track reports of targets using a statistical model that is capable of:

  • Clustered detections

  • Unclustered detections

  • False alarms

  • Random noise

radarDataGenerator is configured so that:

  • The field of view is rectangular

  • Clutter is unfiltered and an identification number is provided for each clutter element

  • Each radar in the scenario observes the same scatters

radarScenario for this application supports:

  • Multiple clutter patches managed by SurfaceManager

  • Multipath reflections for targets in free space

  • Atmospheric refraction defined by atmosphere object

Surfaces are defined as landSurface, seaSurface, or customSurface objects and support:

clutterGenerator default "Uniform" ScattererDistribution supports:

Waveform-Level Simulation

Waveform-level simulations account for the signal and data processing chain and generate high-fidelity I/Q signals. You can use constantGammaClutter and gpuConstantGammaClutter to quickly model I/Q signals of surface clutter. If you want to model targets in clutter, use radarTransceiver as part of a radar scenario with sensor and target platforms. Waveform-level applications that incorporate clutter include:

  • Algorithm design and testing

  • End-to-end analysis of radar systems

This tables provides information on waveform-level surface clutter models, capabilities, and simulation approaches available in Radar Toolbox, organized by application.

ApplicationHow to Model Using Radar ToolboxExamplesAdditional Information

Simulate large amounts of surface clutter as I/Q signals to:

  • Design and test clutter mitigation algorithms

  • Train AI networks

Use constantGammaClutter and gpuConstantGammaClutter to quickly model I/Q signals of clutter.

constantGammaClutter and gpuConstantGammaClutter assumes:

Return the gamma value for built-in terrain types using surfacegamma.

Plot the angle-Doppler response of the simulated clutter using phased.AngleDopplerResponse.

Simulate pulse-Doppler I/Q signals of targets in clutter within a dynamic scenario to:

  • Perform end-to-end analysis of pulse-Doppler radars

  • Design and test clutter mitigation algorithms

Use radarTransceiver as part of a radarScenario with clutterGenerator enabled and set ScattererDistribution to "RangeDopplerCells" to model I/Q signals in a dynamic scenario using a faster range-Doppler-adaptive approach.

radarTransceiver with clutterGenerator "RangeDopplerCells" enabled assumes:

  • Flat Earth

  • Free space propagation

  • Smooth surface

radarScenario for this application supports:

Surfaces in this scenario are defined as landSurface, seaSurface, or customSurface objects and support:

clutterGenerator "RangeDopplerCells" ScattererDistribution supports:

Simulate high-fidelity I/Q signals of targets in clutter within a dynamic scenario to:

  • Perform end-to-end, site-specific analysis

  • Design and test clutter mitigation algorithms

  • Design and test algorithms for SAR

  • Simulate clutter from moving sea surfaces

Use radarTransceiver as part of a radarScenario with clutterGenerator enabled and set ScattererDistribution to default "Uniform" to model high-fidelity I/Q signals in a dynamic scenario.

radarTransceiver with clutterGenerator "Uniform" supports:

  • Curved Earth

  • Atmospheric refraction

  • Site-specific digital terrain elevation data

radarScenario for this application supports:

Surfaces in this scenario are defined as landSurface, seaSurface, or customSurface objects and support:

clutterGenerator default "Uniform" ScattererDistribution supports:

Normalized Radar Cross Section (NRCS)

Normalized Radar Cross Section (NRCS) is a dimensionless quantity that provides a measure of the reflectivity of a surface, per unit area. Use built-in surface models available in landreflectivity, seareflectivity, and surfaceReflectivity to determine NRCS. surfaceReflectivity system objects were specifically designed to support radarScenario. Surface models are generally grazing angle dependent. Clutter elements in the models have a Gaussian distribution, meaning that discrete clutter elements, such as buildings or individual trees, are not modeled.

landreflectivity and surfaceReflectivityLand contain several land models (Barton, Billingsley, APL, GIT, Morchin, Nathanson, ConstantGamma, and UlabyDobson). Although most land models are considered to be polarization independent, theUlabyDobson model incorporates polarization. Each land model supports multiple land types that are valid over predefined grazing angles and frequencies (see Land Reflectivity Models and Land Types). landroughness returns properties of the Barton model, including height standard deviation, slope, and vegetation type. The figure below shows NRCS as a function of grazing angle for two land types.

seareflectivity and surfaceReflectivitySea contain several sea models (NRL, APL, GIT, Hybrid, Masuko, Nathanson, RRE, Sittrop, and TSC) that are polarization dependent. Sea surface models are valid over predefined grazing angles and frequencies (see Sea Reflectivity Models) and account for the radar look angle, which is defined with respect to the wind direction (the look angle is zero when the radar is pointed upwind). searoughness returns model height standard deviation, slope, and wind velocity for a given sea state or wind scale.

Radar Cross Section (RCS)

Radar Cross Section (RCS) is a measure of the amount of energy returned from a surface, in units of area. RCS is a function of the radar's frequency, grazing angle, and range and depends on the surface NRCS. Surfaces with larger NRCS reflect more strongly and thus return more powerful clutter echoes. Use clutterSurfaceRCS and clutterSurfaceRangeDopplerRCS to calculate surface RCS. Clutter patch RCS is calculated internally during a radarScenario simulation.

clutterSurfaceRCS calculates clutter using a Beam-Illuminated Approximation or Pulse-Illuminated Approximation approximation. Beam-limited clutter tends to occur at high grazing angles and pulse-limited clutter tends to occur at low grazing angles. See Beam-Limited and Pulse-Limited Clutter. The Radar Designer app uses the same calculations for RCS as clutterSurfaceRCS.

clutterSurfaceRangeDopplerRCS describes the distribution of surface clutter over range and Doppler space and supports Doppler wrapping (see RCS with Doppler Wrapping). See Range-Doppler Cells in Cartesian Space and Range-Doppler Map (RDM) for more information on the distribution of surface clutter in range-Doppler space relative to Cartesian space. Clutter I/Q simulated with "RangeDopplerCells" enabled in clutterGenerator as part of a radarScenario are equivalent to those generated using the clutterSurfaceRangeDopplerRCS RCS in a custom simulation demonstrated in Predict Surface Clutter Power in Range-Doppler Space.

radarScenario determines clutter patch RCS within the scenario simulation using information contained in landSurface, seaSurface, and customSurface objects. Land/sea/custom surfaces in the scenario are managed by surfaceManager and contain surfaceReflectivity objects that support uncorrelated, multiplicative speckle. The addition of speckle makes clutter appear noisier for imaging applications.

clutterGenerator Scatterer Distribution and Regions

Attach clutterGenerator to a radarScenario to model surface clutter radar returns in radarTransceiver and radarDataGenerator simulations. Clutter returns emanate from landSurface, seaSurface, and customSurface objects in the scenario. Land/sea/custom surfaces are managed by surfaceManager and contain surfaceReflectivity objects. Introduction to Radar Scenario Clutter Simulation details how to generate monostatic surface clutter signals and detections in a radar scenario.

clutterGenerator approximates reflections from large continuous surfaces as a set of point scatterers. When the ScattererDistribution property is set to the default value of "Uniform", the Resolution property determines the density of clutter patches using perturbed grid points (see Perturbed Grid Patching). When the ScattererDistribution property of clutterGenerator is set to "RangeDopplerCells" (this selection is compatible with radarTransceiver but not radarDataGenerator), a faster range-Doppler-adaptive approach is used in which one clutter scatterer per range-Doppler resolution cell is modeled. The NumRepetitions property or the radarTransceiver, along with the radar's PRF, determines the Doppler resolution of the adaptive scatterers.

You can designate specific clutter regions in clutterGenerator. Set UseBeam to true to automatically generate mainlobe clutter (see Mainlobe Clutter). You can also call ringClutterRegion on the clutter generator object to specify ring-shaped clutter regions within which clutter is generated (see Ring-Shaped Clutter Regions).

Perturbed Grid Patching

clutterGenerator approximates reflections from large continuous surfaces as a set of point scatterers using perturbed grid patching. This method involves perturbing a set of grid points pseudo-randomly and results in scatterers that have a fairly uniform density that are sufficiently randomized to achieve a robust Monte Carlo integration. The figure below shows original grid points in blue and perturbed points in red.

The clutterGenerator Resolution property determines the nominal spacing of clutter patches. A smaller nominal resolution value results in more scatterers per unit area. The nominal resolution value should be set to the smallest expected ground resolution of the radar system over the clutter regions of interest to get at least one scatterer per resolution cell. Ideally, you should model eight scatterers per resolution cell. Decreasing the Resolution value results in more scatters per resolution cell. The down-range resolution corresponds to the radar's range resolution and is therefore a fixed value. The cross-range resolution is determined by the radar's beamwidth and the distance to the target. Typically, the down-range resolution is smaller (better) than the across-range resolution, which depends on slant range.

Mainlobe Clutter

The UseBeam property enables the modeling of mainlobe clutter, or unwanted reflections that originate from the antenna pattern, based on the shape of the beam footprint. The beam footprint is the projection of a beam of a given beamwidth onto a surface.

Most phased arrays supported by radarTransceiver and clutterGenerator have a conical beamshape and an elliptical normalized footprint that is assumed to have a 3 dB beamwidth in both azimuth and elevation. phased.ULA has a fan-shaped beamshape that is also supported and is assumed to have a 3 dB beamwidth in the plane perpendicular to the array axis.

radarDataGenerator has a rectangular field of view, with azimuth and elevation set by the FieldOfView property. clutterGenerator supports this rectangular beamshape.

Ring-Shaped Clutter Regions

You can call ringClutterRegion on the clutter generator object to specify custom-sized ring-shaped clutter regions within which clutter is generated. A ring clutter region is defined by a minimum and maximum ground range and an extent and center angle in azimuth. These regions are useful for capturing sidelobe and backlobe clutter return, mainlobe clutter return outside the 3 dB beamwidth (for a radarTransceiver phased array), or to generate clutter from any other region of interest, such as at the location of a target platform. Because radarDataGenerator is a statistics-based detectability simulator and does not contain a complete antenna pattern, clutter modeling is limited to the mainlobe only. To enable clutter simulation for radarDataGenerator, set the UseBeam property to true.

The figure below illustrates two ring clutter regions, one directly underneath the radar for capturing altitude return, and another for capturing some backlobe clutter return. The beam footprint region for the radarTransceiver phased array is displayed as a magenta ellipse where the beam intersects the ground. See Introduction to Radar Scenario Clutter Simulation for more information.

References

[1] Barton, David Knox. Radar Equations for Modern Radar. Artech House, Boston, 2013.