1.
Focus on M-sequence sensor electronics
IR-UWB: Correlator
-Jayendra Mishra

2.
UWB Principle Of Operation
 Ultra-wideband sensors stimulate their
test objects with pulses.
 UWB pulses allows following the
propagation and the temporal
development of energy distribution
within the test scenario
 Multiple chirp signals of sub
nanoseconds spread over a large
bandwidth are generated to get an
impulse response.

3.
Measurement Complexity
 Large peak power signals represents some inconvenience of the
impulse measurement technique.
 Idea is to go away from excitations by strong single or infrequent
‘shocks’ and to pass instead to a stimulation of the DUT by many subtle
‘pinpricks’.
 Binary pseudo-noise codes represent pulse signals which are more
careful with the test objects.

4.
Binary
Pseudo-Noise
Codes
 Pulse signals which have spread their energy homogenously over the whole signal length. Hence, their
peak voltage remains quite small by keeping sufficient stimulation power.
 PN-codes are periodic signals which constitute of a large number of individual pulses ostensible
randomly distributed within the period. The theory of PN-code generation is closely connected with
Galois-fields and primitive polynomials.
 Summarized by the term binary PN-code they may have three (-1, 0, 1) and more signal levels.
 Amalgamated properties of two signal classes
 Periodic-deterministic signals
 Random signals
 Pseudo-noise codes examples: Barker code, M-sequence, Golay-Sequence, Gold-code, Kasami-code

5.
M-Sequence
 Maximum length binary sequence or shortly
termed M-sequence is Simple to generate
and provide best properties to measure the
Impulse response function IRF.
 For a given signal power, lowest amplitude
and shortest autocorrelation function.
 No. of flip-flops in shift register determine
the length of M-sequence
 Spares the measurement objects and the
requirements onto the receiver dynamic
are more relaxed.

6.
M-sequence Generation
 Digital shift registers with appropriate
feedbacks.
 Shift the starting point of the M-
sequence to control the time lag of an
UWB correlator.
 In figure the register is of the 9th order.
 Fibonacci structure deals with cascaded
XOR-gates which increase the dead time
before a new change of the flip-flop
states is allowed.

7.
Technical
Challenges
 IRF measurement not directly possible with a time extended
signal such as the M-sequence.
 The M-sequence signal has to be subjected to an impulse
compression to gain the wanted impulse response.
 The price to pay for reduced voltage in a UWB signal is the
chaotic structure of the receive signal, therefore, a correlator
is required for interpretation.
 Intermediate frequency cannot provide a low freq. as the
Nyquist bandwidth is huge for 3 GHz of bandwidth.
 To perform the correlation of a very wideband signal we
need.
 Cross-correlation to access the wanted IRF
 Digital impulse compression
 Frequency domain conversion

8.
Impulse
Correlator
 Objective: to determine the impulse response function of a
test object.
 A correlator is used to detect the presence of signals with a
known waveform in a noisy background.
 The output is nearly zero (below set threshold) if only noise
is present.
 Impulse compression is performed by the correlator

9.
Impulse
Correlation
 In UWB, Impulse compression using wideband correlation
 Convolving with a time inverted stimulus x(-t).
 Technical implementation Cross-correlation
 The Sliding correlator
 PN- correlation

10.
The Sliding
Correlator
 (a.1) Two shift registers of identical behavior make a
sliding correlator. First one provides actual band
limited stimulus signal at fc, and second serves as
reference to perform correlation fs = fc-Δf.
 (a.2) Both shift registers have to run in parallel with
constant time lag during this time.
 (b.1) Integrator of the product detector is crucial for
the noise suppression and it largely determines the
overall sensitivity of the sensor device.
 (b.2) Waveform sweeping over the initial states of
each of the shift registers to get sampled version of
correlation function. Rather sliding, the correlator
jumps in steps of Δtc = 𝑓𝑐−1
.
 This gives sampled version of correlation function.
 Sampling interval equals the M-sequence chip
duration.

11.
Block Diagram Of UWB Correlator
 Digital ultra-wideband correlation joins
sliding correlator and stroboscopic
sampling.
 Sub-sampling: data gathering is
distributed over several periods by
capturing the signal with the lower
sampling rate fs.
 Since No. of chips: Ns = N = 2 𝑛
− 1 ,n is
the order. sub sampling is simply
controlled by a binary divider.
 The placement of the anti-aliasing filter
depends on the measurement
environment.

12.
Sub-Sampling Control By Binary Divider.
 Goal is in to organize a precise and simple sub-
sampling control.
 Interleaved sampling approach for single stage
binary divider; so, two stage divider would have
four periods of measurements.
 In figure, 3rd order M-sequence with 7 chips or
data samples.
 For every beat of the clock generator the voltage
is captured at every second beat.
 So, first the odd chip numbers are captured and
then the even ones.
Wanted results: IRF or FRF of DUT.

13.
Data Reduction By Averaging
 the most efficient way permitting both a
high sampling rate and a continuous
processing of the incoming data stream.
 Shorter the binary divider, higher the
efficiency.
 Synchronous averaging- used before
applying other cascaded linear algorithms
for data reduction.
 the total number of data samples reduces by
the factor p, Synchronous averaging
performs noise suppression by the factor √p.

14.
Digital Impulse
Compression
 If only round trip time is of interest we can apply
correlation between receive signal y(t) and the ideal
m-sequence m(t), for faster implementation. Where
IRF shape is less important.
 The known M sequence data samples arranged in the
circulant matrix Mcirc are rearranged in Hadamard
matrix for faster computing in Fast Hadamard
transform (FHT). Figure shows the Hadamard butterfly.
 ENOB-number of receiver that includes the
quantization noise and the thermal noise.
 FHT-butterfly is used which only includes sum or
difference operations which can be executed at high
processing speed.
 the correlation leads to a noise suppression by the
factor √Ns = √(2 𝑛
-1). The equation shown in figure is
equivalent to the signal with Max. SNR obtained afte
FFT or FHT operation.

15.
Design Tetrahedron Of Digital Ultra-Wideband
Correlator
Binary divider length- relaxes the speed requirements onto
the receiver. Large dividing factor reduces data throughput
but also largely reduces sensitivity of receiver.
Recording time Tr- number p of averaging controls
recording time length. Target speed and acceleration, and
the rate of mechanical object oscillations are the dominant
parameters restricting the recording time in radar
measurements.
Pre-processing- An M-sequence sensor is typically
equipped with FPGA for data processing as
• Data reduction by averaging or Background removal
• Digital impulse compression or correlation
• Data conversion into frequency domain and error
correction, detection; round trip time estimation.

16.
KNOCK YOUR SELF OUT!