ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets n Read 4.3 n Problems 4.10, Web 8...

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ECEN5633 Radar Theory ECEN5633 Radar Theory Lecture #22 2 April 2015 Lecture #22 2 April 2015 Dr. George Scheets Dr. George Scheets www.okstate.edu/elec-eng/scheets/e www.okstate.edu/elec-eng/scheets/e cen5633 cen5633 Read 4.3 Read 4.3 Problems 4.10, Web 8 & 9 Problems 4.10, Web 8 & 9 Design Problem due 7 April (Live), 9 April (DL) Design Problem due 7 April (Live), 9 April (DL) Late turn in fee = -1 per working day Late turn in fee = -1 per working day Reworked exams due 14 April (Live) Reworked exams due 14 April (Live) Quiz #2 Results Quiz #2 Results Hi = 13.6, Low = 6.50, Ave = 11.33, Hi = 13.6, Low = 6.50, Ave = 11.33, σ σ =2.71 =2.71

Transcript of ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets n Read 4.3 n Problems 4.10, Web 8...

Page 1: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

ECEN5633 Radar TheoryECEN5633 Radar TheoryLecture #22 2 April 2015Lecture #22 2 April 2015Dr. George ScheetsDr. George Scheetswww.okstate.edu/elec-eng/scheets/ecen5633www.okstate.edu/elec-eng/scheets/ecen5633

ECEN5633 Radar TheoryECEN5633 Radar TheoryLecture #22 2 April 2015Lecture #22 2 April 2015Dr. George ScheetsDr. George Scheetswww.okstate.edu/elec-eng/scheets/ecen5633www.okstate.edu/elec-eng/scheets/ecen5633

Read 4.3Read 4.3 Problems 4.10, Web 8 & 9Problems 4.10, Web 8 & 9 Design Problem due 7 April (Live), 9 April (DL)Design Problem due 7 April (Live), 9 April (DL)

Late turn in fee = -1 per working dayLate turn in fee = -1 per working day Reworked exams due 14 April (Live)Reworked exams due 14 April (Live) Quiz #2 ResultsQuiz #2 Results

Hi = 13.6, Low = 6.50, Ave = 11.33, Hi = 13.6, Low = 6.50, Ave = 11.33, σσ =2.71 =2.71

Page 2: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

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Page 3: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Coherent DetectionCoherent Detection RCVR Local OscillatorRCVR Local Oscillator

PLL seeks echo frequency & phase lockPLL seeks echo frequency & phase lockttpp = 1 = 1 μμsec, fsec, fcc = 10 GHz → 10,000 cycles = 10 GHz → 10,000 cycles

Will take some time Will take some time Some echo energy is lost Some echo energy is lost Matched Filter fed sinusoid until lockMatched Filter fed sinusoid until lock

Area around zeroArea around zero

Locked → Matched Filter fed baseband pulse Locked → Matched Filter fed baseband pulse Best Potential PerformanceBest Potential Performance

Page 4: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Non-coherent DetectionNon-coherent Detection

RCVR Local Oscillator at transmitted fRCVR Local Oscillator at transmitted fcc

Stationary target with respect to radarStationary target with respect to radarZero doppler, baseband pulse to Matched FilterZero doppler, baseband pulse to Matched Filter

Moving target with respect to radarMoving target with respect to radarWide variety of signals fed to Matched FilterWide variety of signals fed to Matched Filter

May get almost nothing when sampledMay get almost nothing when sampled Quadrature DetectionQuadrature Detection

If energy not in I channel, it's in Q channelIf energy not in I channel, it's in Q channel

Page 5: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Ambiguity FunctionAmbiguity Function

X(X(ττ,,νν) = g(t)g*(t - ) = g(t)g*(t - ττ) e) ej2j2πνπνt t dtdt

X(X(ττ,0) = Autocorrelation ,0) = Autocorrelation of complex envelope g(t)of complex envelope g(t)

= Matched Filter output envelope= Matched Filter output envelope at Zero dopplerat Zero doppler

X(0,X(0,νν) = F.T. of signal's magnitude (AM)) = F.T. of signal's magnitude (AM)

∫-∞

+∞

Page 6: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Ambiguity FunctionAmbiguity Function

X(X(ττ,,νν) = g(t)g*(t - ) = g(t)g*(t - ττ) e) ej2j2πνπνt t dtdt

For most accurate range estimatesFor most accurate range estimates Want narrow width along Want narrow width along ττ (time) axis (time) axis

For most accurate radial velocity estimateFor most accurate radial velocity estimate Want narrow width along Want narrow width along νν (frequency) axis (frequency) axis

Since X(0,0) = 1 &Since X(0,0) = 1 &Volume of |X(Volume of |X(ττ,,νν)|)|22 = 1 (if complex E = 1) = 1 (if complex E = 1)May not be able to do both May not be able to do both

∫-∞

+∞

Page 7: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Selected e IntegralsSelected e Integrals

Page 8: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Gaussian Pulse Ambiguity FunctionGaussian Pulse Ambiguity Function ttpp = 1.0 = 1.0

source: west 5633 notes

Page 9: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Matched Filter Outputs as fd ↑ Matched Filter Outputs as fd ↑

fd = 1

fd = 2fd = 3

fd = 5

Page 10: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.

Rectangular Pulse Ambiguity FunctionRectangular Pulse Ambiguity Function

source: skolnik, Introduction to Radar Systems

Page 11: ECEN5633 Radar Theory Lecture #22 2 April 2015 Dr. George Scheets  n Read 4.3 n Problems 4.10, Web 8 & 9 n Design.