Ch1.Introduction+to+Radar+Systems(70)

RADAR SIGNAL PROCESSING LAB.KOREA AEROSPACE UNIV.

Radar Signal ProcessingGraduate Course

Prof. Young K Kwag


Chapter 1

Introduction to Radar Systems

Fundamentals of RSP


RADAR: Radio detection and rangingEarly history of radar extends to the early days of modern electromagnetic theory

•In 1886 : Hertz demonstrated reflection of radio waves•In 1900 : Tesla described a concept for electromagnetic detection and velocity measurement•In 1903 and 1904 : German engineer Hülsmeyer experimented with ship detection by radio wave reflection• In 1922 : Marconi advocated this idea again• In 1934 : Setting off a more substantial investigation that led to a U.S. patent for what would now be called a Continuous Wave (CW) radar

1.1 History and Applications of Radar


ApplicationsApplications of Radar• Police traffic radar

: Enforce speed limit and measure the speed of baseballs and tennis serves• Color weather radar

: Viewer of local television news: One type of metrological radar

• Air traffic control: Guide commercial aircraft both an route and in the vicinity of airports: Determine altitude and avoid severe weather: Image runway approaches in poor weather: Collision avoidance and buoy detection by ships

• Spaceborne (both satellite and space shuttle) and airborne radar: Map earth topology and environmental characteristics


1.2 Basic Radar Functions

)1.1( 2

0ctR =

Radar equation

; c=the speed of light=3*108

angleelevationangleazimuth

::

φθ


Basic Radar Functions

Velocity is estimated by measuring the Doppler shift of the target echoes. Radar Functions :

- Detection and Tracking- Generate two-dimensional images of an area- analysis of earth resources issues such as mapping, land

use, ice cover analysis, deforestation monitoring.- “terrain following” navigation by correlating measured

imagery with stored maps.The quality of a radar system: probability of detection PD probability of false alarm PFA

- if other system parameters are fixed, increasing PD always requires accepting a higher PFA

- determined by signal-to-interference ratio (SIR)


Radar Signal Processing Functions

- High probability of detection PD ,

Low probability of false alarm PFA

- Improve SIR by pulse integration

- Improve resolution and SIR by pulse compression

- Improve accuracy by increased SIR and “filter splitting”

interpolation methods

- Improve side lobe behavior with windowing techniques


Basic Radar Signal Processing Functions

Radar signal processing draws on many of the same techniques- Linear filtering and statistical detection theory- Fast Fourier Transform (FFT)- Modern model-based spectral estimation - Adaptive filtering techniques (beam-forming, jammer cancellation)- Pattern recognition techniques (target/clutter discrimination)Radar signals have very high dynamic ranges of several tens of decibels, in some extreme cases approaching 100dB. Thus, gain control schemes are common, and side lobe control is often critical to avoid having weak signals masked by stronger ones. Radar signal bandwidths are larger than most other DSP applications.- some high resolution radars : several hundred MHz, and even as high as

1GHz


1.3 Elements of a Pulsed Radar


Transmitter

Waveform generator- To generate the desired pulse waveform

Transmitter- To modulate the pulse signal to the desired radio frequency (RF)

- To amplifies this signal to a useful power level

Duplexer- Through the duplexer, transmitter output is routed to the antenna

- To be also called circulator or T/R switch


Receiver

Low-noise RF amplifier- First stage of receiver

Mixer and Local Oscillator (LO)- Received signal is modulated intermediate frequencies (IF) and to baseband

Signal Processor- Baseband signal is next sent to the signal processor

- Signal processing: pulse compression, matched filtering, Doppler filtering, integration, CFAR detection, Clustering, motion compensation, and so on.

Data processor & Display- The signal processed is sent to the system display and/or data processor


1.3.1 Transmitter & Waveform Generator

Operational Frequency

- 2MHz ~ 220GHz

- Laser radar:

→ on the order of 1012 to 1015 Hz

- Most radar:

→ about 200MHz to about 95 GHz

Millimeter wave band

- To be decomposed:

→ Q band: 36 to 46 GHz

→ V band: 46 to 56 GHz

→ W band: 56 to 100 GHz


Atmospheric Attenuation

Frequencies above X bandAtmospheric window- Most Ka band radar system operates : near 35GHz- Most W band radar system operates : near 95 GHz


Operational FrequencyLower radar frequencies- Longer range surveillance application- Because of : → low atmospheric attenuation→ high available powers

Higher radar frequencies- High resolution and shorter range application- Due to :→ smaller achievable antenna beamwidth (for a given antenna size)→ higher attenuation→ lower available powers

radians89.0beamwidth dB-3 3yDλθ ≈≡ (1.9)


Weather conditions

Atmospheric attenuation for rain ratesX-band and below- To be affected significantly only by very severe rainfall

Millimeter wave - To have severe losses for even light-to-medium rain rates


The most important properties for a signal processing - Gain, Beamwidth, Sidelobe-levels

We can get the factors from the antenna power pattern,

The antenna power pattern

1.3.2 Antennas

),( φθE : electric field in antenna voltage pattern

One dimensional pattern for a rectangular aperture

2),(),( φθφθ EP = (1.3)

)()(),( φθφθ φθ PPP = (1.4)


Let’s consider only the far-field power pattern

Azimuth pattern

; A(y)= current , It is invert Fourier Transform of A(y)

∫−⎥⎦⎤

⎢⎣⎡

=2/

2/

sin2

)()( y

y

D

D

yjdyeyAE

θλπ

θ (1.5)

Figure 1.5 Geometry for one-dimensional electric field calculation on a rectangular aperture

Antenna pattern


[ ](1.8)

sin)/(sin)/(sin

θλπθλπ

y

y

DD

=∫−⎥⎦⎤

⎢⎣⎡

=2/

2/

sin2

)()( y

y

D

D

yjdyeyAE

θλπ

θ

Antenna pattern


Numerically, α=1.4 which gives the value of θ at the -3 dB point as

θo=0.445 λ/Dy. The 3-dB beamwidth extends from –θo to +θo

radians 89.0 4.1sin2 beamwidth 3 13

yy DDdB λ

πλθ ≈⎟⎟⎠

⎞⎜⎜⎝

⎛=≡− − (1.9)

The angular resolution of the antenna is determined by the 3-dB beamwidth of its main lobe.

This can be founded by 707.02

1)( ≈=θE

Note : a smaller beamwidth requires a larger aperture or a shorter wavelength.

3-dB Beamwidth

and solving the argument α=π(Dy/λ)sinθ.


If a wave with power density W W/m2 is incident on the antenna ,

and the power delivered to the antenna load is P

m 2

WPAapertureEffective e = (1.11)

Effective Aperture and Gain

- Effective aperture is related to antenna directivity, which is related to

antenna gain and efficiency.

The effective aperture and gain are related by

4 2 eAGλπ

= (1.12)


It is composed of array elements that is identical dipoles or other simple antennas with very broad patterns.

Usually, the elements are evenly spaced to form a uniform linear array.

Array antenna

Figure 1.7 Geometry of the uniform linear array antenna


The voltage pattern for the linear array

)( eout voltag totalThe1

0

sin )/2(0∑

−

=

=N

n

ndjneaEE θλπθ

This is similar to the discrete Fourier transform of the weight sequence {an}.

In case of all an =1, the pattern is the familiar “aliased sinc” function, whose magnitude is

[ ][ ]

sin)/(sinsin)/(sin)( 0 θλπ

θλπθddNEE =

Array antenna pattern

(1.13)

- There are N elements in the array- The elements are isotropic (unity gain for all θ). - The signal branch n is weighted with the complex weight an.- Incoming electric field is Eoexp(jΩt) at the reference element

(1.14)


The echo waveform r(t) received from a single scatterer

1.3.3 Receivers

[ ] )(sin)()( tttAtr θ+Ω=

- the amplitude modulation A(t) represents the pulse envelope.

(1.17)

Quadrature channel receiver


I-channel (the lower branch) mixes the received signal with the local

oscillator (LO)

The mixer output is

[ ] [ ] [ ] )(2cos)()(cos)()(sin)()sin(2 tttAttAtttAt θθθ +Ω−=+ΩΩ

The sum term is then removed by the low-pass filter, leaving only the

modulation term A(t)cos[θ(t)].

Q-channel (the upper branch) mixes the signal with the LO having the same frequency but a 90° phase shift from the I channel oscillator. The mixer output is

[ ] [ ] [ ] )(2sin)()(sin)()(sin)()cos(2 tttAttAtttAt θθθ +Ω+=+ΩΩ

(1.18)

(1.19)


Which, after filtering, leaves the modulation term A(t)sin[θ(t)].


The reason that both the I and Q channels are needed



We can use equivalent complex exponential function for the echo signal of (1.17)

[ ] )()( )(ttjetAtr θ+Ω=

Now, the Fig.1.9 (I-Q channel block diagram) can be replaced

Fig.1.9 implies several requirement on a high-quality receiver design.

- a single stable local oscillator (STALO) to provide a frequency reference for both the transmitter and the receiver.

(1.21)[ ])(sin)()( tttAtr θ+Ω=

Complex Exponential Function


- coherent operation. Coherency is a stronger requirement than frequency stability.

In practice, it means that the transmitted carrier signal must have a fixed phase reference for several, perhaps many, consecutive pulses.

High-quality Coherent Receiver


- I and Q channels have perfectly matched transfer functions over the signal bandwidth. Thus, the gain through each of the two signal paths must be identical, as must be the phase delay (electrical length) of the two channels.

- the oscillators used to demodulate the I and Q channels must be exactly in quadrature, that is, 90º out of phase with one another.

High-quality receiver design


The received signal is amplified upon reception using a low-noise amplifier

(LNA). It determines the noise figure of overall receiver.

The key figure of the superheterodyne receiver is that the modulation to

baseband occurs in two or more stages.

Superheterodyne receiver

Superheterodyne Receiver


Resolution Cell

the volume in the spacethat contributes to the echo received by radar at any one instant

increases with the square of rangetwo-dimensional spreading of beam at longer range

1.4.1 Resolution

RRRRRV Δ=Δ=Δ 33233

4)

2)(

2( ϕθπϕθπ

VΔ


Range resolution

The quantity that Separate different two targetinto different time samples in the range direction.

1.4.1 Resolution

22)(

200 ττ ctcctR =−=Δ−


Cross-range resolution (Angular resolution)

The distance between two targets located at the 3dB edges of the beam.

Provided that the main lobe width is 3dB beamwidth of the antenna.

1.4.1 Resolution

33)

2sin(2 θθ RRCR ≈=Δ


Wavenumber

Time domain

Spatial domain

1.4.2 Spatial frequency

cT λ=

λcF =(sec)

λπc2

=(Herz) (rad/sec)

λ=Tλ1

=F(meter)λπ2

=(cycles/meter) (rad/meter)

Wavenumber


Quantization

Process of mapping the continuous signal

to one of a finite set of values.

Number of bits determine Number of values.

1.4.4 The sampling theorem


Nyquist sampling theorem

Nyquist criterion requires at least two samplesper period of the highest frequency component.

More direct interpretation is thatthe sampling frequency should be greater thanthe total spectral width of the of the signal.


FsF β>

Nyquist criterion


Reconstruction of the signal

1) Sampling model x(u) is multiplied by impulse train

2) Fourier transform of Sampling signal

)]()[(


∑∞

−∞=−=

nsDs nTuuxx δ

∑ ∑∞

−∞=

∞

−∞=

−=−=n

ns

ss kFUX

TkUXUX )()()(

SpectrumReplication


Reconstruction of the signal

3) Reconstruct X(U) by lowpass filtering

Reconstruction of original spectrum X(U) isequivalent to reconstructing x(u).Since a signal and its Fourier transformform a unique one-to-one pair.


Low pass filter


1.5 Preview of Basic Radar Signal Processing

Ch.4 : matched filter maximizeSNR – until the detector is considered, important to maximize SNR

Fig.1.23 : easier to understandthe motivation for, and interrelation of, many of the processingoperations

Generic radar signal processor - signal conditioning- interference suppression- imaging- detection- postprocessing


1.5.1 Radar Time Scales

Operation : applied to data from a singlepulse occur on the shortest time scale

• as fast time because the sample rate,determined by the instantaneous pulsebandwidth

• Corresponding sampling intervals range from a few microseconds down to a fraction of a nanosecond

• order of hundreds of kHz to few GHz• Typical fast time operations :

- I/Q signal formation - beamforming, - pulse compression- matched filtering, - sensitivity time control


1.5.1 Radar Time ScalesOperation : data from multiple pulses

• Sampling interval between pulses : PRI• order of tens of microseconds to hundreds of milliseconds • Slow time operation :

- coherent and noncoherent integration, - Doppler processingsynthetic aperture imaging- space-time adaptive processing

Higher level of radar processing : multiple CPIs (longer time scales)- order of milliseconds to ones or tens of seconds- multiple-CPI ambiguity resolution techniques- multilook SAR imaging Track filtering- track filtering


1.5.2 Phenomenology

To design a successful signal processor → characteristics of the signalsPhenomenology : the characteristics of the signals received by the radar

(signal power, frequency, polarization, angle of arrival)

The received signal phenomenology is determined by- Physical size or orientation and velocity- The characteristics of the radar (ex. transmitted waveform, polarization)

In Ch.2, models of the behavior of typical measured signals - radar range equation : predicting signal power- Doppler phenomenon : received frequency- random process and linear systems theory : describe radar signals and

to design and analyze radar signal processors


1.5.3 signal conditioning and interference suppression

Signal conditioning operations

1.First several blocks after the antenna in Fig. 1.23

2.Purpose is to improve the SIR

3.Combination

- Fixed and adaptive beamforming

- Pulse compression

- Clutter filtering

- Doppler processing


BeamformingFixed beamforming

1.Form a directive gain pattern, similar to that shown in Fig. 1.6

2.The high-gain main lobe and low side lobes

- Selectively enhance the echo strength from scatterers in the antenna look

direction while suppressing the echoes from scatterers in other directions

3.Proper choice of the weights

- The main lobe can be steered to various look directions

- Tradeoff between the side lobe level and the main lobe width can be varied


BeamformingAdaptive beamforming- Greater jammer and clutter suppression

Step of the adaptive beamforming1.Recognize the presence of jamming and clutter entering the antenna pattern

side lobes

2.Design a set of weights for combining the channels

- High-gain main lobe and low side lobes

- Null in the antenna pattern at the angle of arrival of the jammer


Example of the effect adaptive beamforming

Fig 1.25 Example of effect adaptive beamforming. (a) Map of received signal power as a function of angle of arrival and signal Doppler shift. (b) Angle-Doppler map after adaptive processing. (Image courtesy of Dr. W. L. Melvin.)

Beamforming


Pulse compression is a special case of matched filtering

Relation to high sensitivity in detecting targets and high rangeresolution• The transmitted energy increases : Target detectability improves

• The transmitted waveform’s instantaneous bandwidth increases : Range resolution improves

• Example) Constant-frequency rectangular envelope pulse as its transmitted

waveform, then the pulse is lengthened

- Increase the transmitted energy ⇒ Increasing the target detectability

- Decreases its instantaneous bandwidth ⇒ Degrading the range resolution⇒Thus, sensitivity and range resolution appear to be in conflict

with one anther

Pulse compression


Pulse compression- Provides a way out of this dilemma by decoupling the waveform bandwidth

from its duration- Design a modulated waveform- Common choice is the linear frequency modulated (linear FM, LFM, or “chirp”)

Pulse compression

Fig 1.26 (a) Linear FM waveform modulation function, showing an increasing instantaneous frequency. (b) Output of the matched filter for the LFM waveform of (a)


Matched filter - Designed to maximize the SNR at its output- Impulse response of the filter

: Turns out to be a replica of the transmitted waveform’s modulation function (reverse in time and conjugate)

-Thus, the impulse response is “matched” to the particular transmitted waveformmodulation

Pulse compression-A single point scatterer concentrated most of its energy in a very short duration-Thus, provide both the good range resolution and the high transmitted energy of a long pulse -The 3-dB width of the main lobe in time is approximately 1/β seconds,

where β is the instantaneous bandwidth of the waveform usedRange resolution

Pulse compression

β2cR =Δ


Clutter filtering and Doppler processingClutter filtering and Doppler processing- Improving the detectability of moving targets by suppressing interference

from clutter echoes- Based on differences in the Doppler shift of the echoes form the clutter and

from the targets of interest

Clutter filtering- Moving Target Indication, or MTI- Simply pulse-to-pulse highpass filtering of the radar echoes , which are

assumed to be due to nonmoving clutter

Doppler processing- Use of the fast Fourier transform algorithms, or occasionally some other

spectral estimation technique- Due to their different Doppler shifts, the target is detected and separated


1.5.4 ImagingRadar

- Produce “blips” on a screen to represent targets- Detect and track moving targets- Compute high-resolution images of a scene

Comparison of photograph and radar image•Photograph- Easier for a human to interpret and analyze

•Radar image- Monochromatic- Less detail- Exhibit a “speckled” texture- Image a scene through clouds and inclement weather due to the superior propagation of RF wavelengths

- Image equally well 24 hours a day


Imaging

Fig 1.27 Comparison of optical and SAR image of the Albuquerque airport. (a) Ku band (15 GHz) SAR image, 3-m resolution. (b) Aerial photograph (Images courtesy of Sandia National Laboratories.)

Comparison of optical and SAR image


Imaging

Fig 1.28 National images of the Albuquerque airport that might be obtained if the experiment of Fig. 1.27 were repeated on rainy night (a) Radar image. (b) Simulated aerial photograph. (Radar image courtesy of Sandia national Laboratories.)

Comparison of optical and SAR image on rainy night


ImagingObtain high-resolution imagery- High-bandwidth waveforms in the range dimension

- Synthetic Aperture Radar (SAR) technique in the cross-range dimension

Real aperture radar- Nonimaging radar

- The resolution in cross-range is determined by the width of the antenna beam

at the range of interest

3θR (1.22)Δcross-range resolution =

- If Beamwidths : 1°~3° or 17~52 mradRange : 10 km

- Poor cross-range resolution is overcome by using SAR techniques

⇒Cross-range resolution = 170~520 m


Synthetic aperture technique

Fig 1.29 The concept of synthetic aperture radar

Synthetic aperture technique- Concept of synthesizing the effect of a very large antenna by having the

actual physical radar antenna move- Associated with moving airborne or space-based radar


1.5.5 DetectionSignal processor- Analyze the total received signal

- Determine the desirable target echo

Threshold detection- Detection of target echoes in the presence of competing interference signals is

a problem in statistical decision theory

- The technique of threshold detection is the optimal performance

- The magnitude of sample of the radar echo signal (after conditioning and

interference suppression) is compared to a precomputed threshold

signal amplitude < threshold : Interference signals only

signal amplitude > threshold : Presence of a target echo in addition to the

interference ⇒ Detection or “hit” is declared


Detection

Fig 1.30 Illustration of threshold detection.

False alarm- A noise spike could cross the threshold, loading to a false target declaration

- False alarm is smaller ⇒ SIR is larger


Detection

Constant-False-Alarm Rate (CFAR) detection- Limit false alarms to an acceptable rate

- The required threshold is estimated using interference statistics estimated

from the data itself

Pulse compression- The matched filter maximizes the SIR, providing the best threshold detection

performance

- Thus, the technique of pulse compression is important so that high resolution

can be obtained while maintaining good detection performance


1.5.6 PostprocessingPostprocessing operation is referred to as data processing

Tracking- Detect the presence of targets

- Estimate the range and angle of the target

- The angle measurements are obtained using angle tracking techniques,

especially monopulse tracking

- Provide a snapshot of the target location at one instant in time

- Track filtering describes a higher-level process of integrating a series

(such measurements to compute a complete trajectory of the target motion)


1.6 Radar literature

This part introduces the text to radar system and the current radar research

1. Radar systems and components

2. Radar signal processing

3. Advanced radar signal processing

4. Current radar research


1.6.1 Radar systems and components

Principles Of Modern Radar- Author : Jerry Eaves, Edward Reedy - Publisher : Springer (June 30, 1987)- ISBN : 0442221045 - Contents : Most classic introductory

Introduction to Radar Systems 3rd edition- Author : Merrrill I. Skolnik- Publisher: McGraw-Hill Companies (August 15, 2000)- ISBN: 0072909803 - Contents : Most classic introductory text to radar systems


1.6.1 Radar systems and components

Radar: Principles, Technology, Applications- Author : Byron Edde- Publisher : Prentice Hall Ptr (September 24, 1992)- ISBN : 0137523467 - Contents : Introduction of several general radar system

Radar Principles- Author : Peyton Z. Peebles- Publisher : Wiley-Interscience (September 29, 1998) - ISBN : 0471252050 - Contents : Recent, comprehensive introduction


1.6.1 Radar systems and componentsRadar Systems Analysis and Design Using MATLAB 2nd edition- Author : Bassem R. Mahafza- Publisher : Chapman & Hall/CRC (March 9, 2005) - ISBN : 1584885327 - Contents : Useful MATLAB

Airborne Pulsed Doppler Radar (Artech House Radar Library) 2nd edition - Author : Guy V. Morris, Linda Harkness- Publisher : Artech House Publishers (November 1996) - ISBN : 0890068674- Contents : Introduction to airborne pulsed Doppler systems


1.6.2 Radar signal processingRadar Design Principles: Signal Processing and the Environment2nd edition- Author : Fred E. Nathanson- Publisher : Mcgraw-Hill (Tx) (January 1991) - ISBN : 0070460523

- Contents : Radar system in general, but concentrate on signal processing

issues (RCS and clutter modeling, waveforms, MTI, and detection)

Radar Principles - Author : Nadav Levanon- Publisher : Wiley-Interscience (May 5, 1988) - ISBN : 0471858811- Contents : Analyses of many basic signal processing functions


1.6.2 Radar signal processingRadar Signals- Author : Nadav Levanon, Eli Mozeson- Publisher : Wiley-Interscience (July 1, 2004) - ISBN : 0471473782 - Contents : Widening variety of radar waveforms in detail

Microwave Radar: Imaging and Advanced Processing- Author : Roger J. Sullivan- Publisher : Artech House Publishers (June 2000) - ISBN : 0890063419 - Contents : SAR and space-time adaptive processing (STAP)


1.6.3 Advanced radar signal processingSynthetic Aperture Radar: Systems and Signal Processing(Wiley Series in Remote Sensing and Image Processing) - Author : John C. Curlander, Robert N. McDonough- Publisher : Wiley-Interscience (November 1991) - ISBN : 047185770X- Contents : First comprehensive text about SAR

: Emphasize space-based SAR and include a strong component of scattering theory

Digital Processing Of Synthetic Aperture Radar Data : AlgorithmsAnd Implementation (Artech House Remote Sensing Library)- Author : Ian G. Cumming, Frank H. Wong- Publisher : Artech House Publishers (January 2005) - ISBN : 1580530583- Contents : Newest SAR text, emphasize spaced-based SAR


1.6.3 Advanced radar signal processingSpotlight Synthetic Aperture Radar: Signal Processing Algorithms(Artech House Remote Sensing Library)- Author : Walter G. Carrara, Ronald M. Majewski, Ron S. Goodman- Publisher : Artech House Publishers (October 1995) - ISBN : 0890067287- Contents : Group at the Environmental research institute of Michigan

: Spotlight SAR modeSpotlight-Mode Synthetic Aperture Radar : A Signal Processing Approach- Author : Daniel E. Wahl, Paul H. Eichel, Dennis C. Ghiglia, Paul A. Thompson- Publisher : Springer (January 31, 1996) - ISBN : 0792396774- Contents : Group at Sandia National Laboratories

: Spotlight SAR mode


1.6.3 Advanced radar signal processing

Synthetic Aperture Radar Signal Processing with MATLAB Algorithms- Author : Mehrdad Soumekh- Publisher : Wiley-Interscience (April 13, 1999) - ISBN : 0471297062 - Contents : Using MATLAB

Synthetic Aperture Radar Processing- Author : Giorgio Franceschetti, Riccardo Lanari- Publisher : CRC (March 30, 1999) - ISBN : 0849378990- Contents : Strip-map and spotlight SAR mode


1.6.3 Advanced radar signal processingSpace-time adaptive processing- Author : Richard Klemm- Publisher : Inspec/Iee (December 1998) - ISBN : 0852969465- Contents : First significant open literature text on STAP

Space-Time Adaptive Processing for Radar (Artech House Radar Library)- Author : J. R. Guerci- Publisher : Artech House Publishers (August 2003) - ISBN : 1580533779 - Contents : Newest primer on STAP


1.6.3 Advanced radar signal processingOptimum Array Processing (Detection, Estimation, and ModulationTheory, Part IV) - Author : Harry L. Van Trees- Publisher : Wiley-Interscience (March 22, 2002) - ISBN : 0471093904- Contents : Detection and estimation about STAP

: More limited forms of adaptive interference rejection

Radar Signal Processing and Adaptive Systems 2nd Edition - Author : Ramon Nitzberg- Publisher : Artech House Publishers (June 1999) - ISBN : 1580530346- Contents : Side lobe canceller


1.6.4 Current radar researchIn United states

Institute of Electrical and Electronics Engineers (IEEE)

Transactions on Aerospace and electronics Systems

Transactions on Geoscience and Remote Sensing

Transactions on Image Processing

In United Kingdom

Institution of Electrical Engineers (IEE)

Proceedings : Radar, Sonar, and Navigation

Ch1.Introduction+to+Radar+Systems(70)

Documents

airborne radar

color weather radar

basic radar functions1

early history of radar

korea aerospace univ

radar equation c

basic radar functions

radio detection