Robert E. Zarnich ASTO D1 zarnichre@navsea.navy.mil

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• In the History of War the Submarine
Commanding Officer is the only Blind
Combatant
• Combat System Information
Dependent on Processing but
Commonly Checked Visually
• The Sonar is the Eyes of the
Submarine
• ‘Broadband’ Sonar is Context
– Scene Management
• Desired Characteristics of
‘Broadband’
– Summary of All Contacts
– Intuitive Format
– Detail vs Clutter (PD vs PFA) Situational Awareness
new
Time
~60
min
old
forward cos(Bearing) aft
(0 relative) (180 relative)

Array
Data
Beamform
(1) Spectral Weight
Second Generation Passive Broadband
Spectral
Weight
(1)
Spatial
Normalizer
(2)
Non-Linear
Quantization
(3)
Display
w-spectral(f,t) = f( E[ SNR(f),t ] ) - BQQ-5 used 2 modes of fixed Eckart Weighting
with 3 integration times*
(2) Spatial Normalizer
w-spatial(θ n,t) = g(θ n-D, … , θ n-O, θ n+O, … , θ n-D, t) - Split Window Averages with a
Gap
(3) Non - Linear Quantization
w-power = h( CDF(Power)) - Fixed Histogram Intensity Map
* Fixed “Optimal” Weighting Proved Not Be- A Major Deficiency
Processing Reminiscent of H0 vs H1 Single Signal Testing followed
by a Graphical Rendering of Test Statistic

Major Changes
Third Generation Passive Broadband
• Recognition of Change in Threat Bands of Interest and Environment
• Clutter Mitigation Through Resolution
• Adaptive Beamforming
Contact of Interest

Array
Data
Fore-Aft
Beamform
(1)
(1) Front-Aft Beamforming
Third Generation Passive Broadband cont.
Temporal
Whitening
(2)
Correlation Based
Correlation
Interpolation
(3)
Quantize
&
Display
Adaptive Beamformer. Array Split into First N/2 and Second N/2 Elements, Highly
Overlapped. Beam Space, 7 DOF, Distortionless, with Single Pattern Soft Const.
(2) Temporal Whitening - Smoothed Coherence Transform (SCOT), (Carter et.al.)
w(B M(FORE) , B M(AFT),f,t) =
⎜⎛
BM ( Fore)
( f , t)
* BM
( Aft ) ( f , t)
⎝
(3) Interpolation - Up-Sample to Smooth Coarse Information - Improves Visual Quality
High Resolution in Bearing Space
Eliminates ‘Wash-Out’ Effects of Strong Narrow Band Interferers
Stable Through Maneuvers:
Self Normalization and Reduced Array Distortion Mismatch (Half Aperture)
⎟⎞
⎠
−1

Array
Data
Beamform
Third Generation Passive Broadband cont.
Normalize
Peak Pick
(1)
Fine Bearing
Interp
(2)
(1) Normalize and Peak Pick in Frequency
Sub-band Peak Energy Detection (SPED)
Coarse Normalization (De-trend) and Identify all Peaks over Clutter Threshold.
(2) Fine Bearing Interpolation
Peak assigned to Best Bearing in Grid. Grid Size > # Elements
(3) Accumulate over Frequency
Sum over Frequency. 2 Methods, Binary and Power
(4) Spatial Normalizer
Accumulate
over Freq
(3)
Spatial
Normalizer
(4)
Quantize
&
Display
w-spatial(θ n,t) = g(θ n-D, … , θ n-O, θ n+O, … , θ n-D, t) - Split Window Averages with a Gap
High Resolution in Bearing
Able to Eliminate ‘Wash-Out’ Effects of Strong Narrow Band Interferers, While
Retaining Sensitivity to Narrow-Band Dominated Contacts

True
Spatial Spectrum
Spatial Spectrum
Freq vs Bearing
Power->Color
Peak Picked
Spatial Spectrum
Summed Peaks
Summed Raw Spectrum
(Scan)
Summed Raw Spectrum
Summed Peaks
Power
Freq
Freq
Power
20
0
-20
20
40
20
40
20
0
-20
SPED Processing Example - Rx Known
48 Element Array, 6 Signals, 44 Frequency Bins, 400 Bearing Bins,
Flat Temporal Spectrum
-3 -2 -1 0 1 2 3 4
-3 -2 -1 0 1 2 3
-3 -2 -1 0 1 2 3
-3 -2 -1 0 1 2 3
-3 -2 -1 0 1 2 3 4
W a ve Nu m b e r * fo /f
0
-10
-20
0
-10
-20
15
10
5
0
PP Sum
Raw Sum

Observations
• Deduction - Broadband is Fundamentally a Direction Finding Problem
– Direction Finding is:
First - Signal Detection
Second - Signal Direction of Arrival Estimation
– Good Direction Finding is Sensitive, Highly Resolved and Precise
• Why are the New Techniques Working
– Detail Not Clutter, Resolution is Everything
– Not Constructed as a “Matched Receiver/Detector”, More Data, Less Theory
• Optimality versus Robustness - Always a Trade Off
– Matching Expected Spectrum to Targets of Interest is not Practical, Targets
Change, More Importantly The Environment is Anything but Fixed
– Submarine Sonar Must Find Things Other than Submarines, e.g. P-D
• Thesis - Room for Performance Enhancement if The ‘Intent’ of the SPED
‘Broadband Process’ Were Maintained With Support From a Higher
Resolution Front End
– More Like Direction Finding Than Beamforming

Array
Data
Covariance
Estimate
Fourth Generation Passive Broadband ?
Generalized Direction Finding Based ‘Broadband’
Direction
Finding
Accumulate
over Bands
Spatial
Equalization
Quantize
&
Display
Objective - Exploit SPED’s Concept with Higher Resolution Front End and Novel
Accumulation Schemes While Providing Robust Performance Even During Turns
Covariance Estimate - 20 second Exponentiated Average, Exploit Conjugate Symmetry,
add -10dB Diagonal Loading Relative to Average Element Power. (Experimentation)
Direction Finding - Quadratic Spectral Capon Estimation (MVDR) With ~10*N Samples
From -1 to 1 in u-space. Subspace Approach, Spectral MUSIC, Had Major Sensitivities To
Model Order Variations.
Accumulate Over Bands - Power Summing Method Chosen Based On Empirical Results.
Spatial Equalization - Traditional Technique Avoided Due to Limited Time to Prepare and
Runtime Impact. Non-Traditional Technique Discussed During Graphic
Quantize & Display - 10*log10(Accumulated Power), MATLAB imagesc for Rendering

Representative Data Case III
ED - CS Band 1 ED Band 1 CC Band 1

Representative Data Case III
ED Band 1 Spectral DF Based BB 5sec Rx Band 1

5 sec. R x
Bounds of Stationarity ?
20 sec. R x

20 sec. R x
Bounds of Stationarity ?
60 sec. R x

Data Case III
ED Band 1 Spectral DF Based BB Band 1

1
0
f start f stop
=
Spectrum?
f start f stop

SSP
Short Course In Ocean Acoustics
Art, Ira, Please Forgive Me

for every cell,
if Cell == BLACK,
Cell = Pea Green
else,
swap(Green, Blue),
Cell = Cell
max(Cell)
end_if
end_for
Data Case III
Maximized Intensity, Neutral Background, (Swap Green and Blue)

Data Case II
ED Band 1 Spectral DF Based BB Band 1

Data Case II

Data Case II
Maximized Intensity

Data Case I
ED Band 1 Spectral DF Based BB Band 1

Data Case I
ED Band 1 DF Based BB Band 1 CC Band 1

Data Case I
ED Band 1 Spectral DF Based BB Band 1

Data Case I
ED Band 1 Spectral DF Based BB Band 1 - Maximized Intensity

Summary
• This Brief Study Indicates There is Still Substantial Processing Gains
Available to Enhance Broadband System Performance
• Thesis That Exploiting Direction Finding Technology Would Enhance
Performance Proved True
• Need Robust Practical Approaches for Exploiting Propagation
Observables Due to Environmental Effects
– Could Quickly Generate Vital Tactical Information
• Work Needed to Extend Integration Time Beyond Integration Periods of
Physical Stationarity and Conventional Wisdom
• Work Needed to Formulate Better Rendering Schemes
– Coloring/‘Normalization’ to Worked But Could be Much Improved
• Thanks
– ASTO/PMS425, CAPT/Dr. J. Polcari
– APB Signal Processing Working Group (SPWG), DSR
– Prof’s K. Bell, H. L. Van Trees
– You for Your Attention