Applied Research Laboratories: The University of Texas at Austin Wideband Monopulse Spatial Filtering for Large Array Receivers for Reverberant Underwater Communication Channels Karl Nieman Applied Research Laboratories: The University of Texas at Austin Kenneth Perrine, Terry Henderson, Keith Lent, Terry Brudner, and Brian Evans IEEE OCEANS 9/22/10

Outline Underwater Acoustic Communications (ACOMMS) Vertical Array ACOMMS Receiver Wideband Monopulse Beamforming Multi-Channel Equalization Multipath Simulation Experimental Results from Lake Travis 9/22/10 K. Nieman, IEEE OCEANS’10 2

ACOMMS with Large Array Receiver Buoys Array Receiver Divers Communicator(s) Seafloor Instruments UUVs 9/22/10 K. Nieman, IEEE OCEANS’10 3

ACOMMS vs. RF Wireless Comms Acoustic propagation speed slower by 200,000X More severe effects of time-varying boundaries and Doppler Absorption-limited bandwidth In 10°C seawater: 1 kHz: ~0.06 dB/km 100 kHz: ~33.4 dB/km USEABLE BAND (at 1 km) 9/22/10 K. Nieman, IEEE OCEANS’10 4

Shallow Water ACOMMS Channel Impairments Severe Doppler may be present Substantial vertical multipath due to boundary reflections Rapidly-varying channel Coherence time is only marginally longer than impulse response duration: absolute amplitude Shallow water impulse response of LFM sweep over 1 s. 9/22/10 K. Nieman, IEEE OCEANS’10 5

ACOMMS Signal Processing Compensating for channel impairments: Detect, synchronize and compensate for Doppler Adaptively equalize Adaptive equalizer size dilemma: Small to maintain stability while tracking quickly-varying paths Large to fully deconvolve long channel response Often, all acoustic paths cannot be coherently combined, leaving residual incoherent paths that degrade performance. Performance is then reverberation limited rather than background-noise limited 9/22/10 K. Nieman, IEEE OCEANS’10 6

Single-Channel ACOMMS Receiver wet dry Frame detection/ synchroni-zation Bulk Doppler detection/ correction Single channel adaptive DFE omni receiver Our configuration: Adaptive Decision Feedback Equalizer (DFE) 11 half-symbol spaced forward taps 5 decision feedback taps Hybrid LS-LMS algorithm with adaptation step size 0.01 4096 M-QAM data symbols per packet Problem: Performance is limited in shallow water Solution: Substitute a large array of closely-spaced elements for omni receiver Use vertical multi-channel processing to combat multipath 9/22/10 K. Nieman, IEEE OCEANS’10 7

ACOMMS Receiver Using Array wet dry Horizontal beamform/select Vertical processing options Frame detection/ synchroni-zation Bulk Doppler detection/ correction K-channel adaptive DFE N layers We compare four vertical processing options: K=N option: Pass all N outputs to DFE K=1 option: Form single vertical beam s0(t) for DFE K=2 option: Form two vertical wideband monopulse beams for DFE K=3 option: Form three vertical wideband monopulse beams for DFE K=N has been addressed by many investigators But often with large vertical element separation Large N can threaten equalizer success K=1,2, or 3 can exploit beamformer capabilities already needed for other purposes 9/22/10 K. Nieman, IEEE OCEANS’10 8

Explanation of Vertical Processing for K =1,2,3 K=1 option: Form single vertical beam output s0(t) Steer to reject bad multipath (e.g. boundary reverberation) K=2 option: Use wideband monopulse processing to get 2nd beam output s1(t) such that s1(t) ≈ α s0(t) where K=3 option: Include a 3rd beam output s2(t) such that s2(t) ≈ α s1(t) sum weight delay N elements Spatial response beamwidth (frequency independent) 9/22/10 K. Nieman, IEEE OCEANS’10 9

Wideband Monopulse Wideband Null Steering Simple linear combination of s0(t) and s1(t) gives single wideband null: Linear combination of s0(t), s1(t), and s2(t) gives two indepedently-steerable wideband nulls Equalizer can form these linear combinations (or any others), in the K=2 and K=3 cases, to best minimize MSE In fact, it does Monopulse method thus reduces the number of input channels to the equalizer yet allows a spatial null(s) to be steered toward localized interferences 0.17s0(t) + s1(t) linear combination 9/22/10 K. Nieman, IEEE OCEANS’10 10

Results of Simulation and In-Water Tests at Lake Travis 9/22/10 K. Nieman, IEEE OCEANS’10 11

Shallow Water Simulation Ray trace from omni-directional source to 6-element vertical line array for different shallow water channels (ranges of 25-700 m) Isotropic sound speed 3 paths (direct, surface bounce, and bottom bounce) source array Performance metric used: output signal-to-noise-ratio (OSNR) Inverse of mean squared error at DFE output Ray trace of propagation paths through isotropic medium. 9/22/10 K. Nieman, IEEE OCEANS’10 12

No Doppler Simulation , K=1 option: K=2 option: K=3 option: K=N option: , OSNR at EQ output for stationary 6-element line array processed using four different techniques. 9/22/10 K. Nieman, IEEE OCEANS’10 13

5 m/s Doppler Simulation K=1 option: K=2 option: K=3 option: K=N option: , OSNR at EQ output for moving 6-element line array processed using four different techniques. 9/22/10 K. Nieman, IEEE OCEANS’10 14

Evidence of Null-Steering in Equalized Channel equalizer length path 1 (direct) path 2 (surface) path 3 (bottom) K=1 LFM matched-filter of EQ-forward filtered output for (a) s0(t), (b) s0(t) + s1(t), and (c) s0(t) + s1(t) + s2(t). Orange and green shaded region shows EQ time span for forward and feedback filter taps, respectively. K=2 K=3 9/16/10 K. Nieman, IEEE OCEANS’10 15

Experimental Data from Lake Travis Two sets of data collected at ARL:UT’s Lake Travis Test Station (LTTS) in 2009 using array receiver + mobile, omni source Overhead view of Lake Travis Test Station with overlaid bathymetric map. 9/16/10 K. Nieman, IEEE OCEANS’10 16

Test A: 6-Element Vertical Line Array Evaluated gain in OSNR of K=2 re: K=1 vs. range Just as in simulation, gains are highly dependent on range (multipath structure), and decrease with increasing range OSNR gain of s1(t) + s0(t) vs. s0(t) for 155 16QAM packets. Results sorted by range (red dots, right vertical axis). 9/22/10 K. Nieman, IEEE OCEANS’10 17

Test B: 8-Element Vertical Line Array Gain vs. single-element receiver for each technique K=2,3 have similar mean to K=N w/ less variance Also, 1-2 orders of magnitude less complexity in DFE alone K=N K=3 K=2 K=1 OSNR gain and ±σ over single element receiver for four processing methods for 96 packets at various rates. 9/22/10 K. Nieman, IEEE OCEANS’10 18

Closing Remarks Conclusions Caveats K=2,3 can reduce the size/complexity of the equalizer w/ similar performance to K=N in shallow water Smaller equalizer can be stable w/ increased adaptation rate Outperforms straight beamforming (K=1) in all data Caveats Observed gains dependent on: multipath environment (e.g. range, depths) platform motion May not do as well w/ uniform interference 9/22/10 K. Nieman, IEEE OCEANS’10 19

Questions? References: [1] – R. E. Francois and G. R. Garrison, “Sound absorption based on ocean measurements – 2. boric acid contribution and equation for total absorption,” J. Acoust. Soc. Am., vol. 72, no. 6, pp. 1879-1890, 1982. [2] – K. A. Perrine, K. F. Nieman, K. H. Lent, T. L. Henderson, T. J. Brudner, B. L. Evans, “Doppler estimation and correction for shallow underwater acoustic communications,” Proc. Asilomar Conf. on Signals, Systems, and Computers, 2010. [3] – K. F. Nieman, K. A. Perrine, K. H. Lent, T. L. Henderson, T. J. Brudner, B. L. Evans, “Multi-stage and sparse equalizer design for communication systems in reverberant underwater channels,” Proc. IEEE Int. Workshop on Signal Processing Systems, 2010. [4] – P. J. Beaujean and L. R. LeBlanc, “Adaptive array processing for high speed acoustic communication in shallow water,” IEEE J. of Oceanic Engineering, vol. 29, no. 3, pp. 807-823, 2004. [5] – T. L. Henderson, “Matched beam theory for unambiguous broadband direction finding,” J. Acoust. Soc. Am., vol. 78, no. 2, pp. 563-574, 1985. Also, our group has released underwater acoustic data recorded at Lake Travis for public use: http://users.ece.utexas.edu/~bevans/projects/underwater/datasets/index.html 9/22/10 K. Nieman, IEEE OCEANS’10 20

Bad Doppler Example The phase of a QPSK signal after linear Doppler correction. 9/22/10 K. Nieman, IEEE OCEANS’10 21

Data Packet Data packet with durations in symbol periods

Wideband Monopulse ACOMMS Receiver For this study, multi-channel decision-feedback EQ configured with: 11 half-symbol-spaced forward taps per channel 5 symbol-spaced decision-feedback taps LMS adaptation rate of 0.01 data packet 9/22/10 K. Nieman, IEEE OCEANS’10 23