Wavelet Analysis of Low Observable Targets Within Sea Clutter

Wavelet Analysis of Low Observable Targets Within Sea Clutter G Davidson,H D Griffiths University College London Overview       2 Aim is to detect low observable, slow moving targets (debris, ships, others) in heavy sea clutter, within clutter Doppler spectrum. 3GHz and 9GHz real aperture, experimental multifunction radars at metre resolution (QinetiQ). Either the sea surface or the observing platform is moving and, this non-stationary velocity spectrum can mask targets of unknown varying velocity. Strong clutter backscatter complicates CFAR detection. Doppler spectrum is analysed by a Wavelet transform to minimise the uncertainty in both time and velocity. Clutter returns appear to consist of discrete scatterers with a characteristic lifetime. Thresholding this scatterer lifetime reveals a real target in real clutter that was difficult to detect in Intensity and Doppler. This is not the correlation time of the surface. Glen Davidson - Radar 2002 Medium Sea Surface 4.3 metres Significant Wave Height  3 Whitecaps suggest different scattering event Glen Davidson - Radar 2002 Heavy Sea Surface 6.1 metres Significant Wave Height  4 Heavy seas cause shadowing Glen Davidson - Radar 2002 Recorded dB Backscatter 5 Glen Davidson - Radar 2002 Non-Stationary Doppler - Velocity + Dsitribution Proportion Measure Above Noise 6 Time - Velocity + Glen Davidson - Radar 2002 - Velocity + Event Based Processing       Some justification for considering the backscatter as discrete events – these are more obvious in Doppler. Over sufficient time (~30s), these events average out to a stable Doppler spectrum. At shorter time scales (1s) identifying individual events may be useful for target detection. But neither the velocity or the lifetime of the scatterers can be known a priori. Windowed Fourier is not well suited to this. Wavelet Transform is useful for this case as it maintains constant uncertainty in time-frequency. WT gives optimally smoothed Doppler Velocity-Time image of the sea surface. Glen Davidson - Radar 2002 7 Fourier vs Wavelet Transform Convolved Frequency Time Fourier  Arbitrary time window  Window determines frequency  Problems at boundaries 8 Time Wavelet  Forced constant t  Can choose frequency subset  Convolution over all time Glen Davidson - Radar 2002 Wavelet Filter Bank  9 Filter width proportional to frequency, log spaced filter bank Glen Davidson - Radar 2002 Simulated Target (No Noise) FT1 Velocity Measure FT3 Time FT2 Time WT    10 For stable, well defined signals FFT is best, but… At low PRF (1 second of 256 samples) the optimum window size for the Fourier transform (F1, F2, F3) is unknown. The Wavelet transform (WT) gives an acceptable view. Glen Davidson - Radar 2002 Target Parameters Velocity Time Intensity  11 Target simulated from observed parameters (Swerling 1-2) Glen Davidson - Radar 2002 Wavelet Maxima Full Doppler via FFT Power Velocity Doppler via WT Velocity  12 Time Single FFT Doppler is misleading, but WT maxima useful Glen Davidson - Radar 2002 Real Clutter/Simulated Target Real Clutter + 0dB Sim. Target (within clutter spectrum) Velocity Time Real Clutter Time Velocity  13 Doppler is misleading, but WT maxima useful Glen Davidson - Radar 2002 Detection Scheme     Instantaneous WT-Doppler spectrum is smooth (red). Dominant event can be isolated without any thresholding Length of dominant event (arrow) related to individual scatterer lifetime Threshold this to reveal target 14 Glen Davidson - Radar 2002 Lifetime Distribution 20 minutes of data  15 Exponential distributed scatterer lifetime, agrees with Doppler spectral lineshape models [Lee et al.] Glen Davidson - Radar 2002 Log10 Complementary Cumulative Distribution Real Data + 0dB Sim.Target 3GHz, VV 156Hz prf Grazing angle Real Data Scatterer Lifetime Doppler Real Clutter+Target 9GHz, VV 6m Range Resolution 500Hz prf Significant wave ht. 2.4m 8ms-1 wind 1.5 angle (grazing) dB Intensity 16 Glen Davidson - Radar 2002 Intensity Real Clutter+Target Arbitrary Intensity 17 Glen Davidson - Radar 2002 WT Real Clutter+Target Lifetime 18 Glen Davidson - Radar 2002 Conclusions        19 The sea surface backscatter can be considered as a collection of individual scattering events. Event velocity and lifetime unknown so wavelet analysis is easier than FFT Doppler especially for fading targets with velocity varying over ~1 second. WT minimises uncertainty in time and velocity. Dominant scatterer lifetime can be easily measured, distribution is exponential in agreement with models. Thresholding the lifetime of scattering events suggests targets can be detected within the Doppler spectrum. Real data and real target gave encouraging results. Obviously, FFT/MTI is better for fast moving targets of relatively constant velocity outside clutter spectrum. The lifetime of these is determined by the range cell size. Not measuring correlation length – this averages all scatterers together and requires sampling window to be chosen. Glen Davidson - Radar 2002