REAL APERTURE IMAGE GENERATION AND CORRELATION

STUDY

Karthik G.S : 1MV08TE020

Karthik K.S : 1MV08TE021

Kishore K : 1MV08TE023

External Guide ─ Professor Dr G. JagadeeshInternal Guide ─ Ms Roopa K (Sr. Lecturer)

Real aperture image Generation and correlation study

AIM: To generate radar images as obtained from a missile onboard seeker and use them to apply correlation technique with respect to digitally stored image data for extended target detection.

• The study involves generating missile onboard seeker radar image based on simplified geometry and radar parameters as function of different Grazing angles and positions in a missile trajectory.

• Then the generated images are digitally correlated with stored image data to obtain 2D intensity plot of correlation.

•The correlation plots provide the angular errors developed  over the flight time of the approaching missile which is then used to correct the flight path during terminal guidance.

• This work is to be done using visualization and computation application software with image processing tools (MATLAB).It is software intensive work with application to missile terminal guidance.

PHASES OF WORK COVERED

• Development of radar image simulation tool

• Implementation of algorithm for image intensity

• Results for Test case involving runway /city landscape

RADAR

• RADAR is an abbreviation for RAdio Detection And Ranging.

• Uses modulated waveforms and directive antennas to transmit electromagnetic energy into a specific volume in space to search for targets.

• Objects (targets) within a search volume will reflect portions of this energy (radar returns or echoes) back to the radar.

• Echoes are then processed by the radar receiver to extract target information such as range, velocity, angular position, and other target identifying characteristics.

• 2 operational types of Radar: 

Passive Radar

Active Radar

Types of RADARS

• Considering the waveforms used, RADARS can be classified as

Continuous-wave Radars (CW)

Pulsed-Radars (PR)

• CW radars are those that continuously emit electromagnetic energy, and use separate transmit and receive antennas. Target range information cannot be extracted without utilizing some form of modulation.

• Pulsed radars use a train of pulsed waveforms (mainly with modulation).

• In this category, radar systems can be classified on the basis of the Pulse

Repetition Frequency (PRF), as low PRF, medium PRF, and high PRF radars.

• Low PRF radars are primarily used for ranging where target velocity (Doppler shift) is not of interest.

• During each PRI the radar radiates energy only for τ seconds and listens for target returns for the rest of the PRI.

Imaging RADARS

• Imaging radar produces an image in which the digital number(intensity) at each pixel position is determined by the strength of the radar signal reflected from the corresponding location in the scene.

• Imaging radars can be divided in 2 main categories, depending on the imaging technique used:

Real Aperture Radar(RAR)

Synthetic Aperture Radar(SAR).

Real Aperture Radars• Real-aperture radar (RAR) is a form of radar

usually implemented by mounting, on a moving platform

• These are non-coherent which are controlled by the physical length of the antenna

• It is an active radar because it emits little pulses of energy transmitted from the radar antenna to the piece of terrain which we want to obtain the image

• Aperture means the opening used to collect the reflected energy that is used to form an image

• In the case of radar imaging, this is the antenna. For RAR systems, only the amplitude of each echo return is measured and processed

Synthetic Aperture Radars

• SAR or coherent radars generates high resolution images.

• The target is illuminated several times from different locations generating numerous echoes that are recorded coherently (i.e., amplitude and phase as a function of time) and subsequently combined to synthesize a linear array.

• SAR systems can be either airborne or space borne and are much more complex than the RAR systems

Missiles and its types

• A Missile is a self-propelled guided weapon system

• Missile guidance refers to a variety of methods of guiding a missile to its intended target

• Missiles come in types adapted for different purposes: surface-to-surface, air-to-surface (ballistic, cruise, anti-ship, anti-tank), surface-to-air (anti-aircraft and anti-ballistic), air-to-air, and anti-satellite missiles

• Surface to surface missile is considered in the study

Surface to surface missile

Seeker in MissilesWhy seeker in missile?

• Because there is uncertainty in the flight path or target location that makes it impossible to achieve the desired accuracy without a seeker.

• The active radar seeker, from a radar engineer's view, may be defined as an application-specific compact missile-borne pulse tracking radar whose antenna is mounted ,such that the antenna is isolated from the body movement of the missile.

• Active radar seekers are the most popular in all the current missile programs owing to their flexibility of design and implementation to suit almost every mission requirement apart from all weather capability.

Active Radar seeker

Radar Cross Section

• The size and ability of a target to reflect radar energy can be summarized into a single term, σ, known as the radar cross-section(RCS), which has units of m²

• Assume the power density of a wave incident on a target located at range R away from the radar is PDI . The amount of reflected power from the target is:

where σ denotes the target cross section

• RCS forms a strong function of viewing aspect in 3-D

Parameters affecting RCS

• Detection of targets located on the ground, generally poses more serious

challenges because of the randomness of the terrain and the presence of

strongly scattering features on the ground which decreases the SNR of the

backscattered signal, now called clutter.

Radar scattering depends on:

• Dielectric properties (terrain property)

• Conductivity(terrain property)

• Surface roughness/ volume properties (terrain property)

• Incidence angle /Elevation angle(geometric property)

Furthermore dependence on:

• Frequency (radar property)

• Moisture(terrain property)

• Polarization (radar property)

• Motion (geometry/ trajectory)

Parameters affecting RCS

Different surface features exhibit different scattering characteristics:

• Urban areas: very strong backscatter

• Forest: intermediate backscatter

• Calm water: smooth surface, low backscatter

• Rough sea: increased backscatter due to wind and current effects

More wavelength, more penetration

RADAR Targets

There are two types of Radar Target:

• Point targets - Point targets are those targets whose size is smaller than the beam width.

• Higher σ facilitates point target detection.

• Extended targets – Extended targets are those targets whose size is larger than the beam width, complete beam filling.

Backscattering Point Target

Extended Target

POINT TARGET DETECTION

High facilitates point target detection

EXTENDED TARGET DETECTION

Detection based on

RAR SEEKER IMAGE SYNTHESIS

BLOCK DIAGRAM

RAR SEEKER IMAGE SYNTHESIS

• The input includes extended target boundaries, location, nature of target or surroundings and approaching trajectory data.

• The Geometry and Projection block gives the azimuth and elevation angles subtended by the On-board radar with respect to the distributed target of interest, which contributes the Trajectory related information.

• Experimentally obtained database of radar backscatter strength as a function of frequency, polarization, target type and grazing/depression angle are stored and this is used by σ0 computation block as a look-up corresponding to the input data to calculate σ0.

• The Blurring module generates the boundary areas separating the regions of varying backscatter.

• The image generation plot (intensity plot) finally generates the whole frame by weighted averaging method.

Image Generation Procedure• A test image is constructed based

on the geometry of the Landscape and its structures. For example, if a runway is situated in a thickly wooded area, a geometric shape of the runway is drawn with a defined boundary.

• This test image is then dynamically filled with gray scale intensity corresponding to the backscatter strength of the runway and the surroundings.

• For the purpose of generating radar image the rectangular boundaries around distributed target of interest should be specified. Based on this scanning area is marked .

• The scanning interval is the time between two samples taken for processing to generate an image.

•  This time includes the beam acceleration period, uniform scan period and beam deceleration period.

• The radial and azimuthal extent of the surface area that is illuminated by the airborne radar is called as the Radar Footprint.

Common Search patterns used are: Raster Spiral Helical and Nodding (Sinusoidal)

• The intensity pixels in the images are generated by averaging the backscatter intensities over the area illuminated by the beam (foot print area)

• The scan angular rate has to be increased as the onboard radar approaches towards target since as beam footprint shrinks more time is needed to generate the complete frame covering the same area of interest.

Raster Scanning in RAR

• Raster Scanning has been employed in this study.

• Raster scanning is a technique for generating or recording a video image by means of a line-by-line sweep, tantamount to a data mapping scheme between one and two dimensional spaces.

• In raster scanning, the beam sweeps horizontally left-to-right at a steady rate, then blanks and rapidly moves back to the left, where it turns back on and sweeps out the next line.

Search Radar Scan 3D Geometry

Antenna beam footprint scan pattern without overlap

Antenna beam footprint scan pattern without overlap

Imaging Parameters

• Many factors affect the image generation in a typical Real Aperture Radar (RAR).

These factors can be divided into three parameters and they are :

Radar Parameters

Geometry/Trajectory Parameters

Terrain Parameters

Radar parametersThe factors that influence the radar image

formation:

• Beam depth - width of the beam across the scan direction.

• Beam width - width of the beam along the scan direction.

• Scan ellipse - beam footprint projected on to the land surface.

• Scan overlap Factor - factor by which each scan sample overlaps with the other.

• Pixel per unit distance - distance that each pixel in radar represents.

• Pulse width - width of the pulses sent out by radar.

• Frequency Band –frequency band of the RAR operation.

Trajectory Parameters• Elevation angle – The angle of the onboard radar

w.r.t centroid of target patch.• Elevation scan range – The angular range in

elevation plane over which the beam moves.• Azimuth angle - The angle of onboard radar w.r.t

centroid of target patch in azimuth plane.• Azimuth scan range – The angular range in azimuth

plane over which the beam moves• Length & Depth of the rectangular area to be

scanned for imaging.• Radar Range – The radial distance from onboard

radar to centroid of target patch• Scan shift angle – The shift in angle required while

changing scan direction.• Velocity missile – Closing velocity of vehicle

towards impact point.

Terrain Parameters

• Target MCS Number

The gray scale representation of the back scatter signal value (mean clutter strength (MCS)) corresponding to distributed land of interest.

• Background MCS Number

The gray scale representation of the terrain background back scatter signal value.

• Terrain Type

The type of terrain in which the target/structure of interest resides. Also the MCS number includes the effect of propagation in a given atmosphere.

IMPORTANT PARAMETERS

PARAMETER TYPICAL VALUES

Beam Depth and Width ± 4.5 deg

Range resolution 75 m

Scan Rate 64 scans/sec

Pulse Width 0.5 µs

Background Clutter (land ) 20 dB

Target Backscatter () - 5 dB

Terrain type ( variation -25dB to -10 dB) Fields, grass, rocky terrain

Elevation angle scan range +15 to -35 deg

Azimuth angle scan range ± 45 deg

Length of search 60 km

Radar range 60 km max

Velocity 3*e+8

CORRELATION METHODOLOGY(RAR)

• The purpose of the study of Correlation is to evaluate the ‘similarity’ of a chosen ground patch (sub-image) with other parts of a candidate scene, as imaged through a Real Aperture Radar.

• To obtain 2-Dimensional Correlation plots which are used for extended target detection.

• Provides the angular errors developed over the flight time of the approaching missile which is then used to correct the flight path during terminal guidance.

Normalized correlationSeeker generated image

Stored target image on-board

Correlation plots

• Each image is expressed as a matrix of numbers corresponding to the pixel-wise distribution of intensities (Reflectivities) in the image.

• The correlation process then reduces to mathematical operations between the elements of matrices representing the two sub-images being correlated.

• To ensure that the two sub-images being correlated are of equal physical size, it is necessary to ensure that the pixel size in the sub-images is identical.

Correlation Methodology

Correlation methodologyCorrelation (normalized) is performed between the reference subimage and the underlying subimage of equal size, using the formula.

NOTE : The full image and the reference subimage will have identical resolution (i.e., pixel size) for any beam width of the seeker during Correlation process.

h

y

l

xRR

h

y

l

xSSRR

IyxI

IyxIIyxI

C

1 1

2

1 1

,

,,

h

y

h

xRR yxI

hlI

1 1

,1

h

y

l

xSS yxI

hlI

1 1

,1

where

C = Normalized correlation coefficient between the reference sub image and its underlying sub image at a given location

R = intensity (reflectivity) of pixel ( x, y) on the reference sub image

Pixel intensity at xth row and yth column

R , s = Averaged image intensity of reference and underlying subimage

(x,y) = indicates the individual pixel location h, l = height & length (in number of pixels) of the reference subimage

I

I

I

Generic cityscape used as the larger scene

Image of a runway complex which is inserted into the main scene on the bottom right

Composite image used for correlation studies

Composite Image Generation for Test Case Study

Correlation Process stepsThe reference sub image is then shifted by one pixel along the horizontal axis and a fresh correlation coefficient value is obtained. This is repeated till the entire row is exhausted.

The reference sub image is then shifted down by one pixel, and correlated by shifting one pixel at a time along the horizontal axis. The entire scene is thus traversed until the reference sub image reaches the bottom right corner of the larger image.

The value of the correlation coefficient for each position of the reference subimage is plotted as function of the x-y displacement of the subimage from the top left corner of the larger image. This yields a 2-D plot, which is shown as intensity variation over the x-y plane.

The ability of the vehicle to home on to the target based on the reference scene is determined by the ‘uniqueness’ of the reference within the larger image. This, in turn, is demonstrated if the self-correlation of the reference scene is sharp and unambiguous, i.e., there are no other competing peaks of comparable magnitude in the vicinity of the self-correlation peak. In particular, an area of radius equal to the prior guidance error around the self-correlation peak should be free from competing peaks.

The ability of the vehicle to home on to the target based on the reference scene is determined by the ‘uniqueness’ of the reference within the larger image. This, in turn, is demonstrated if the self-correlation of the reference scene is sharp and unambiguous, i.e., there are no other competing peaks of comparable magnitude in the vicinity of the self-correlation peak. In particular, an area of radius equal to the prior guidance error around the self-correlation peak should be free from competing peaks.

Correlation characteristics of the ideal image:

(a) main image showing cityscape with embedded airport feature,

(b) (b) clean subimage containing runways and surrounding areas,

(c) intensity plot of correlation of subimage across main image,

(d) mesh plot of (c), (e) cross-range view of (d),(f) downrange view of (d).

SOFTWARE IMPLEMENTATION

• MATLAB software has been used in this study for generating seeker images in a RAR and then evaluating the similarity between these missile seeker images and the digital images stored in the database of the On-Board computer using the process of correlation.

List of Parameters used in the study

Radar Parameters:

• Beam Depth, Beam Width, Scan Ellipse, Pulse Width, Pixel per Unit Distance and Scan Overlap Factor

Trajectory/Geometry Parameters:

• Elevation Angle (equivalent to grazing angle)

• Length of Stretch

• Radar Range

CASE STUDY ON KARACHI AIRPORT

Clean Scene Stored On-Board

• Read an image (true-color or grayscale) using the MATLAB IPT function imread. Convert this image to a grayscale image if the image is true-color using the IPT function RGB2GRAY. This is the main reference image stored in the database of the On-Board computer in RAR.

• Crop out a portion of this main image to get the target sub-image using the IPT function imcrop. This is used by the RAR as the reference target image.

ALGORITHM

• But for practical cases noise is associated with seeker image generation due to various reasons, one is noise due to electronic sensors in seeker or due to other reasons. So to accommodate for noise and observe the results we add noise (Gaussian noise ) to the main image and using that image we generate a degraded seeker image. Noise is added to the image by using the MATLAB IPT function imnoise.

 

• Load the trajectory parameters (Radar_RANGE)

• IPT function spline is used

• The original trajectory and the trajectory curve obtained by splining is as shown

• Now using the splined trajectory curve obtain Radar_RANGE values at these new points and seeker images are generated at all these points. Seeker images for both main image and target images are generated at all these points by a method of degradation/blurring

• For this purpose, at all these points a structural element is generated using the IPT function getnhood. The radius of this structural element is different at each point in the trajectory(Radar Range) and it is dependent on Pixel per unit distance and Radar Beam-width.

• This structural element (analogous to beam footprint) is used as a template for Raster scanning with overlapping ( as defined by the Overlap_FACTOR) to cover the entire image area. A certain percentage (25%) is used here. The structural element is made to sweep the whole image defined by its own area. At each of these positions the pixels defined by the area of the circle/distorted ellipse are averaged out to get a single value. This process is repeated as the structural element sweeps the entire image area and we get a set of averaged out values which are rounded off.

• This image is the degraded seeker generated image. Thus we generate the seeker generated main image at all points in the trajectory.

 • For the purpose of effective correlation of two images, the two images should have

the same resolution. So we downgrade the clean target scene cropped from the main image to the resolution of the seeker generated image. For this purpose we use the MATLAB IPT function imtransform.

 • At each point in the trajectory, the downgraded target sub-image is correlated with the

seeker generated main image using the IPT MATLAB function normxcorr2 to yield an intensity plot which is the intensity variation of the normalized correlation coefficients over the x-y plane. This plot gives a sharp and an unambiguous intensity peak, providing the angular errors developed over the flight time of the approaching missile which is then used to correct the flight path during terminal guidance.

• To get the mesh plot which is the 3-D view of the intensity plot we use the IPT MATLAB function mesh. The projections of this plot are also obtained using the view MATLAB function.

Conclusion and scope for future work

CONCLUSION

• Thus RAR Imaging is a simple and cost effective technique for missile guidance for extended target detection

THANK YOU