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Digital Alternatives to Analogue Balanced Detection for
Optical Tomography
Rehan Hafiz and Krikor B. Ozanyan
School of Electrical and Electronic Engineering, The University of Manchester.
Manchester M60 1QD, United Kingdom
[email protected]
Abstract. Balanced detection schemes have been used extensively for laser noise removal in
optical measurements, as a method suitable for applications requiring high-sensitivity, e.g.
small signal detection in time and frequency domains or coherent heterodyne detection.
However, the commercially available analogue systems are costly and therefore not suitable for
multi-channel applications, such as tomography. In this work we present a digital alternative,
which can be implemented on general-purpose programmable hardware. The reported
methodology is based on a preliminary calculation of the balancing factor, from the average
power ratio of the signal and reference photocurrents, measured with the object removed from
the signal path. We discuss the performance of three digital processing algorithms for balanced
detection, together with their relevance to particular measurement scenarios. The effect of the
size of the signal averaging window for the power ratio calculation is compared with the
feedback integrating time constant of the existing analogue systems. Simulation and
experimental results are provided to compare the overall performance of the analogue and
digital alternatives. The proposed digital alternatives lead to flexible, scalable, low cost and
compact solutions for multi-channel balanced laser detection systems in general and Optical
Tomography in particular.
1. Introduction
Auto balanced detection schemes have found extensive usage in high-sensitivity small-signal laser
sensing, e.g. in coherent heterodyne detection. It is particularly effective for the removal of laser
intensity noise [1]. However, commercially available analogue implementations are limited by low
bandwidth (125 KHz) and are difficult to integrate in multi-channel applications because of size, cost,
etc. Much easier to integrate would be the digital alternatives which can be implemented on systems
based e.g. on field-programmable logic arrays, with bandwidth limited only by the ADC sampling
frequency and the clock speed of the logic. We propose novel digital sensing methodologies that will
make Auto Balanced Detection feasible for fast computerized optical tomography.
2. Analogue Balanced Detection
In the conventional auto-balanced detection[2], the original laser beam is split into two beams with
some splitting ratio K. One beam (Signal) is passed through the sample while the other beam
(Reference) is passed directly to the detector. Ideally, on the detectors, the reference beam
photocurrent gets the same fractional laser excess noise as the signal beam photocurrent[3]. The two
are then combined in some manner to obtain an output current resulting in substantially suppressed
laser excess noise. The Hobbs auto balancing circuit is widely used for achieving auto-balanced
detection. It has been applied in many commercially available state-of-the-art auto balanced detectors,
such as the New Focus Nirvana auto-balanced detectors [4]. Therefore, the behavior of the proposed
digital balanced algorithm is thus compared with the Nirvana’s output.
3. Digital Balancing Algorithms
Initially, a balancing factor (BF) is calculated from the average power ratio of the signal and reference
photocurrents, measured with the object removed from the signal path. The preliminary calculation of
BF is referred to as calibration in the following discussion. This balancing factor provides the estimate
for the splitting ratio of the beam splitter. Once this ratio is calculated the two beams are then balanced
to achieve balanced detection. After calibration three digital balancing algorithms (DBAx) are
considered for achieving balanced detection.
3.1. Digital Balancing Algorithm 1
In DBA1, point by point division is performed to perform ratio metric detection to remove the
common mode noise. If the beam splitting ratio (K) is not ½, there will be a little offset in the result.
This offset can however be removed using the BF calculated during calibration.
3.2. Digital Balancing Algorithm 2
In DBA2, the point by point ratio is averaged over a sliding window of data stream. The averaging
works to smooth out the shot noise. Again, the BF can be used to remove the offset. Thus the DBA2
gives a much smoother result, as compared to DBA1.
The analogue auto balancing circuitry makes use of a low frequency integrating feedback loop for
gain compensation to balance the two photocurrents[2]. The speed of this feedback loop is a measure
of the time required for the gain compensation circuitry to adjust to changes in reference or signal
power [4]. The analog circuit balances out the low frequency components and acts like a low pass
averaging filter. In the digital alternative, the size of the averaging window works in a similar way, a
smaller size of the averaging window results in a higher bandwidth.
3.3. Digital Balancing Algorithm 3
In DBA3 first the baseline is removed using differentiation and then the noise inter-modulation effects
are ratioed out. It removes common mode noise, as well as additional non-common mode background
noise. Ratio of integrated difference during the calibration gives a measure of background removed
BF, which can be used to measure a constant non-common mode added noise. Assuming that
References signal is not having any non-common mode noise, this method can help in removing any
additional constant background noise that affects only the signal beam.
4. Results
The analogue balancing circuit was simulated with PSPICE and compared with the Matlab
implementations of DBAx. The signal and reference photocurrents were modeled with common-mode
laser intensity noise and some additional uncorrelated noise. The relative strengths of two signals are
shown in Fig.1.a The signal photocurrent carries a very weak two-peak triangular absorption signal.
Fig.1.b and Fig.1.c show that both analogue and digital balancing can distinguish the weak absorption
signal from the large varying noisy background. DBA2 (Fig.1.d) can further reduce the independent
uncorrelated noise (e.g. shot noise), at the cost of time averaging.
Relative Signal Strengths
(c) Digital Balancing output (DBA1)
(b) Analogue Auto balanced output (PSPICE)
Ratio
Ratio
(a) Reference and Signal Photocurrents
(d) Window Averaged Digital Balancing
output (DBA2)
Figure 1 Simulation Results
To perform a practical comparison of the analogue and digital balancing methods the output of the
analogue balancing circuit was directly monitored and stored from the Nirvana log-ratio output using a
digital oscilloscope. For the recorded values of the Nirvana’s outputs, the alternative digital
logarithmic output was calculated offline and later compared with the analogue counterpart.
A 1550nm laser source was first passed through a beam splitter. The strength of the signal beam
was then varied to see the effect of attenuation on the log-ratio output. Figure 2 below shows that logratio auto-balanced output can be achieved using the given algorithms. With the signal strength
decreasing along the x-axis, The Digital and the Analogue outputs are following nearly the same
logarithmic curve. A differential current to voltage converter[5] has already been implemented as a
front end for acquiring the reference and signal photocurrents. The implementation of the above
algorithms on reconfigurable hardware[6] (FPGAs) is underway.
Comparison of Digital and Analogue Log-Ratio Autobalancing
Signal Strength
0
100%
93%
85%
77%
69%
62%
54%
46%
39%
31%
24%
16%
8%
1%
-1
Voltage log-Ratio Ouput (V)
-2
-3
-4
-5
-6
-7
-8
-9
DBD Log-Ratio Output
Nirvana Log-Ratio Output
Figure 2 Experimental comparison of Algorithmic and Analogue version
5. Conclusions and benefits
The digital solutions for the balanced detection provide various advantages over the analogue version.
The output is unaffected by the temperature and other non-linear transient effects of the ICs. The
nature of the algorithms makes them an ideal candidate to be implemented on reconfigurable
hardware. This can allow multiple channels to be implemented on a single hardware, thus directly
reducing the cost and size of the apparatus. The success of digital balancing algorithms expands the
utilization of auto-balancing algorithms for multiple channels applications such as optical tomography.
Real time calculations in reconfigurable hardware can allow easy control logic to be implemented for
the control and automation purposes. The proposed digitally balanced scheme thus provides a flexible,
scalable, inexpensive and compact solution for multi channel imaging systems
References
[1]
NewFocus, "Application Note 14: A Survey of Methods Using Balanced Photodetection".
[2]
P. Hobbs, "Ultrasensitive laser measurements without tears," Applied optics, vol. 36, pp. 903,
1997.
[3]
P. Hobbs, "Shot noise-limited optical measurements at baseband with noisy lasers," Laser
Noise R. Roy, ed., Proc. SPIE 1376, pp. 216-221, 1991.
[4]
New Focus Inc," Nirvana Auto-Balanced Photoreceivers Model 2017 User's Manual", 2002.
[5]
P. Wright, "Design of High-Performance Photodiode Receivers for Optical Tomography,"
IEEE sensors journal, vol. 5, pp. 281, 2005.
[6]
S.Garcia-Castillo and K. B. Ozanyan, "Field-programmable data acquisition and processing
channel for optical tomography systems," Review of Scientific Instruments, vol. 76, 2005.