The Laser Interferometer Space Antenna (LISA) will use Time Delay Interferometry (TDI) to suppress the otherwise dominant laser frequency noise. The technique uses sub-sample interpolation of the recorded optical phase measurements to form a family of interferometric combinations immune to frequency noise. This paper reports on the development of a Pseudo-Random Noise laser ranging system used to measure the sub-sample interpolation time shifts required for TDI operation. The system also includes an optical communication capability that meets the 20 kbps LISA requirement. An experimental demonstration of an integrated LISA phase measurement and ranging system achieved a ≈ 0.19 m rms absolute range error with a 0.5 Hz signal bandwidth, surpassing the 1 m rms LISA specification. The range measurement is limited by mutual interference between the ranging signals exchanged between spacecraft and the interaction of the ranging code with the phase measurement.
©2010 Optical Society of America
The Laser Interferometer Space Antenna (LISA) is a space based mission to detect gravitational waves in the frequency band from 0.1 mHz to 1 Hz. LISA consists of three spacecraft flying in a heliocentric, Earth-trailing orbit, with separations of L = 5 × 109 m. Each spacecraft (SC) contains two proof masses that are shielded from external disturbances. Bidirectional laser links are maintained between all SC in the constellation. The relative optical phase between the incoming and outgoing lasers, referenced to their respective test masses, is used to track the changes in separation between the proof masses, allowing detection of gravitational waves. The change in separation of the proof masses ΔL must be monitored with a displacement sensitivity of to give a strain sensitivity of . This sensitivity requirement far exceeds the stability of available laser sources and has motivated the development of a set of post-processing algorithms termed Time Delay Interferometry (TDI) [1, 2].
The TDI algorithms will provide the majority of the required laser frequency noise suppression through post-processing of the optical phase measurement data recorded at each SC. These sensitive phase measurements are performed by a phasemeter aboard each SC. The phasemeter is required to achieve a relative phase sensitivity of , however this measurement will be limited by shot noise with a spectrum of . The phasemeter provides the input to both the TDI algorithms and ranging system.
The phase data is logged at 3.33 Hz relative to each SC's local clock, however the data streams from all SC must be time synchronised to within ≈ 3 ns (1 m) to achieve the required frequency noise suppression . Without a mechanism for timing synchronisation, a time domain technique called fractional-delay filtering is used to resample the phase data using sub-sample interpolation to synthesise a new set of phase data for all SC relative to a common time base . This technique resamples a SC data stream with respect to a new time reference, accounting for clock differences, propagation delays as required by TDI. Experimental demonstration of one proposed TDI combination on an optical test bed has been shown to provide sufficient frequency noise suppression to meet the LISA requirements with the application of fractional-delay filtering . The interpolation and resampling requires knowledge of the relative time and range between all SC, which is measured using a ranging signal modulated onto each laser link .
In LISA, the ranging signal will be generated by Pseudo-Random Noise (PRN) phase modulation of the bidirectional laser links. This is similar to the Global Positioning System (GPS), which uses PRN modulation of a Radio Frequency carrier for extraction of timing and position . The PRN modulation itself will consist of a deterministic sequence of binary pulses or “chips”, which vary between ±1 in a pseudo-random fashion. An example of a PRN code are the Maximum Length (M) sequence and Gold codes associated with GPS. The LISA PRN modulation will use 1% of the total optical power and will spread this power over a wide (MHz) bandwidth, minimising the interference with the LISA science measurement below 1 Hz. The ranging signal acts as a time stamp upon the laser phase, indicating when the light left the SC. Measurement of the PRN arrival time at the far SC will constitute a ‘pseudo-range’ τ = tTx(t − L/c) − tRx(t), the difference between the receiving SC clock tRx and the transmitted time stamp tTx after propagating at the speed of light c across the arm of length Lm. This measurement is sensitive to two fundamental effects;
- Spacecraft separation L The drift of the LISA arm lengths result in a changing propagation delay T = L/c between SC and appears as a change in the ranging signal arrival time. Any additional physical delay experienced by the ranging signal, such as group delay or dispersion effects, can be thought of as an increase/decrease in SC separation.
- Clock difference tTx − tRx Any differences in spacecraft clocks will cause each SC to generate/measure its ranging signal at a different rate and with a different start time, appearing as an anti-symmetric change in pseudo-range measured between SC.
The use of the pseudo-range measurements for alignment of TDI phase data is best understood by considering the propagation of a pulse of laser frequency noise as it passes through the LISA constellation. For a simple case, we can attempt to cancel a pulse of laser frequency noise leaving SC 1 and arriving at SC 2 using only combinations of phase measurements.
Figure 1 shows the layout of a single LISA arm where a pulse of phase noise ϕ(t) propagates between SC 1 and SC 2. The pulse is recorded by SC 1 as ϕ 1(t 1(t)) = ϕ(t) with local clock time t 1(t) and appears at SC 2, with its local clock t 2(t), after propagation delay L/c = T seconds as ϕ 2(t 2(t)) = ϕ(t − T). The pulse of noise will be cancelled by differencing the SC phase measurements at the time the pulse was measured by each SC, giving ϕ 1(t 1(t)) − ϕ 2(t 2(t) = t 1(t) − T) = 0. In other words, TDI attempts to align each data sample recorded on SC 2 with clock t 2 with an equivalent sample from SC 1, applying sub-sample interpolation where required, such that they a both samples are measuring equivalent phase noise. Determining this alignment requires knowledge of the propagation delay T plus the relationships between the two clocks and is the responsibility of the ranging system.
Since the ranging time stamp is encoded onto the carrier phase, it experiences the same propagation delay T and is recorded with the same clock as the phase data. Correspondingly, the pseudo-range measured at SC 2 is sufficient to identify a) when the sample left SC 1 and b) when it was recorded at SC 2. This implicitly compensates for all physical delays (‘T’) and clock deviations. For each phase sample, the pseudo-range represents the delay/advance that must be applied to align the samples between SC using the fractional-delay filtering approach and represents an equivalent physical range estimate R = cT, for speed of light c. The accuracy of the phase data reconstruction and subsequent frequency noise cancellation is limited by the pseudo-range estimate and is the focus of this paper.
As mentioned previously, another source of physical delay is the analog electronic chain that forms the front end of the phasemeter . This delay is indistinguishable from all other physical delays as measured by the optical signals. It will be correctly (and automatically) measured if the ranging signal and the science signal experience a common delay in passing through the analog chain. A PRN ranging signal centered on the heterodyne frequency will therefore produce the correct total physical delay needed for TDI implementation.
Detection of the PRN ranging signal will use a Delay Locked Loop algorithm comparable to those used by GPS receivers . The receiver generates a local copy of the transmitted code, referred to as the ‘demodulation code’, then attempts to time align it with the incoming ranging signal using a Delay Locked Loop (DLL) to track any timing changes. A nominal chip period of 1 μs is proposed to minimise any differential group delay relative to the MHz frequency heterodyne beat notes. To ensure that the DLL is capable of tracking any timing changes, any averaging performed within the DLL must be significantly faster than the expected timing fluctuations. The digital nature of the PRN modulation also lends itself well to the transmission of data between SC and a 20 kbps data communication requirement has also placed upon the ranging system . Initial simulation work has shown the viability of this scheme for use in the LISA environment .
In this paper, we present a performance prediction and experimental demonstration of an inter-spacecraft ranging algorithm for LISA under expected system conditions. Section 2 introduces the demodulation of the received ranging signal including phase measurement effects and relevant noise sources. Closed loop pseudo-range estimation is presented in Section 3, where we show that the pseudo-range estimate will be limited by cross-correlation between incoming and outgoing PRN codes to ≈ 0.19 m absolute arm length knowledge over a 0.5 Hz signal bandwidth, meeting the 1 m rms LISA requirement. The presented algorithms were integrated into a prototype LISA phasemeter and Section 4 shows the measured ranging performance on a optical test bed, verifying the performance model. A mechanism for optical data transmission is described in Section 5.
2. System Description
In this section we present a model for the demodulation of an incident ranging signal with a local demodulation code. This work builds the previous analysis of the MF-DLL algorithm , extending the model to incorporate several additional effects by including the dispersion effects of the phasemeter, cross-correlation interference and data modulation.
We consider a simplified LISA configuration, concentrating upon the reception of a ranging signal sent from spacecraft SC 2 and received at SC 1 as shown in Fig. 2. PRN ranging codes c 1 and c 2 are phase modulated onto the respective SC lasers via an Electro-Optic Modulator (EOM). The laser from the far SC 2, with phase x 2(t − T) delayed by the propagation delay T, is interfered with the local laser, with phase x 1, at point A 1 on SC 1. The heterodyne beat note, which encodes the difference between the laser phases, is measured at the Detector (D 1) and tracked by the phasemeter. The phasemeter output is passed to the DLL for demodulation of the ranging signal. The outgoing ranging signal is modulated onto the outgoing laser before the interference occurs at A 1.
The LISA lasers will be sufficiently stable that the phase fluctuations are dominated by the ranging modulations c 1 and c 2 ie. x 2 = βc 2 and x 1 = βc 1, with modulation depth β = 0.14rad for 1% of the carrier power. Additionally, over the MHz scale PRN frequencies the LISA phase measurement noise will be dominated by carrier shot noise, appearing as an additive phase noise source νPM with a white spectrum with a value of . At these frequencies, the laser frequency noise is significantly lower than shot noise and will not be considered here.
The difference between spacecraft clocks couples into the phase measurement once the heterodyne beat note is measured with the SC 1 clock t 1. The pseudo-range incorporates the propagation delay T between SC and clock differences and can be viewed as a time varying delay τ 2 applied to the SC 2 laser phase signal. Fortunately, any pseudo-range variations are expected to be slow relative to each pulse period and can be considered static over an averaging period (∼ 50μs). Any long term phase fluctuations will be tracked by the DLL algorithm introduced in Section 3. Setting the global time relative to the SC 1 time t ≡ t 1 gives the shot noise limited phase estimate at the detector as Eq. (1).
2.1. Ranging Demodulation
Recovery of the pseudo-range requires tracking of the ranging signal arrival time. This will be accomplished by the Delay Locked Loop described in Section 3, which forms an error signal by demodulating the ranging signal at two offset timing points. The demodulation mechanism itself is performed by correlating the phase estimate against a local copy of the transmitted code ĉ 2(t, 2) = c 2(t − 2). This local copy, the ‘demodulation’ code, utilises a controllable delay 2 to estimate the pseudo-range delay τ 2 that allows the demodulation code to be aligned with the ranging signal.
The unknown timing differences between LISA spacecraft requires that the initial demodulation delay 2 must be explicitly acquired. Acquisition is accomplished by correlating the phase estimate against the demodulation code while scanning the delay 2, mapping out the auto-correlation of the ranging code. When the misalignment between the demodulation code and ranging signal Δτ 2 = τ 2 − 2 is within 1 chip period TP (|Δτ 2| < TP), a strong correlation peak will be present. The auto-correlation of a PRN sequence evaluated over a period of 50 chips without noise is shown in Fig. 3a, clearly demonstrating the high correlation at 0 delay. While acquisition will not be discussed here, other sources show acquisition within ±1 chip is achievable [7, 9].
After acquisition of the demodulation delay, the correlation between the demodulation code ĉ 2 and phase estimate ϕ 1 can be directly evaluated over an N chip interval for a small acquisition misalignment |Δτ 2| < T P. By assuming that each code chip is represented by a pulse f(t) of width TP and auto-correlation RF(τ), then each chip of the demodulation code will overlap with at most two chips of both the ranging c 2 and interfering c 1 codes.
Figure 3b illustrates the demodulation of an ideal ranging signal without shot noise. The first chip is the ‘wanted’ pulse which correlates with demodulation code and the contribution is N chips weighted by area of overlap. In this instance, the overlap area is defined as , which is the definition the pulse autocorrelation function Rf(.) from Eq. (2) evaluated at the delay Δτ 2. This dependence is also seen in Fig. 3a, where the M sequence auto-correlation follows that of the Rectangular pulse for small offsets. The second ‘unwanted’ correlation results from coupling in an adjacent chip. For sample n, this contribution is given as the code auto-correlation evaluated at a ±1 chip offset C ĉ2,c2 [n, ±1], which is then weighted by the overlap area Rf((Δτ 2 + TP)mod TP).
Similarly, the two pulses introduced by the interfering c 1 code each contribute a cross-correlation term C ĉ2,c1 [n,mi] and C ĉ2,c1 [n,mi + 1], with weightings Rf( 2 mod TP) and Rf(( 2 + 1) mod TP) respectively. Since the interfering code is generated locally, only the changing demodulation delay will affect the alignment with the demodulation code and the cross-correlation will be calculated with an offset mi = ⌊ 2/TP⌋, where ⌊x⌋ is the integer part of x. This determines that the normalised demodulation over N chips (τCorr = NTP), will be given by Eq. (3).
When the misalignment is small (|Δτ 2| ≪ TP), the output is dominated by the strong, coherent signal from the correlation with the ranging signal, with low level cross-correlation noise from the interfering code. As the misalignment increases, the coherent amplitude will reduce down to the noise levels from the other correlation components. To minimise the interference, the cross-correlation between codes c 1 and c 2 should be minimised for all possible delays, however before this effect can be quantified we must discuss the filtering effects introduced by the Phasemeter.
2.2. Phase Measurement Effects and Pulse Shaping
Ideally the phasemeter output would provide a shot noise limited readout of the relative laser phase. In practise, phase measurement algorithms are affected by finite bandwidth and amplitude quantisation, which limit the phase estimate. To track the heterodyne phase, the LISA phasemeter implements a Phase Locked Loop (PLL) with a sophisticated cascade of filters and control systems . Summarised by Fig. 4, the PLL acquires and tracks the phase of the detected heterodyne beat note ϕ 1 through controller CPLL. The detector phase signal is mixed with a Local Oscillator (LO) and low pass filtered (LPF) to form an error signal for feedback control of the LO phase. Such a control system locks the LO to be in quadrature with the signal.
The phasemeter cannot track the fast phase fluctuations of the MHz scale PRN used by LISA. The PLL mixer output (Q) will pass the high frequency PRN modulation signal as phase noise, which the PLL will attempt to suppress. At frequencies well above the control bandwidth the phasemeter passes phase fluctuations through to Q with unity response, however any ranging signal frequency components near or below the phasemeter unity gain frequency will be suppressed and phase shifted. As a consequence, the ranging signal will be filtered by the phasemeter transfer function.
The transfer function between the beat note phase at the photodetector output ϕ 1 and the phasemeter Q channel output ϕQ can be approximated as HPM(s) with Laplace variable s. This transfer function assumes the controller CPLL is dominated by a 1/f slope around the open loop unity gain frequency fu ≈ 100 kHz. The closed loop transfer function exhibits a high pass behaviour, with a corner frequency fu.
For a detector output ϕ 1, then the phasemeter Q output ϕQ(t) will be given by Eq. (4), where the high frequency shot noise is also passed to the output.
This measurement includes the high pass filtering effect through convolution (★) with the phasemeter impulse response hPM. Figure 5a shows the filtering effect upon a Rectangular pulse f(t) of width TP = 1 μs, with an unfiltered pulse shown for comparison. The visible decay induced by the filtering causes a measurable delay in the pulse centroid, which will couple into the range estimate.
To mitigate this effect, the receiver would traditionally match the demodulation code to the filtered signal or include a compensating filter to recover the original pulse shape . These are resource intensive operations. An alternative and complementary solution is to use a Manchester pulse shape, which moves the PRN energy to higher frequencies where the phasemeter transfer function is unity. Manchester encoding of the PRN sequence sends a bipolar pulse of 1, −1 for each code chip and has a pulse shape fM(t) defined by Eq. (5). This pulse shape doubles the signal bandwidth by guaranteeing a transition between 1 and −1 occurs every chip. Additionally, the code is now balanced for each chip, with zero DC component and reduced low frequency information as since each chip has 0 DC power. The Manchester pulse also passes through the phasemeter with minimal decay as shown by Fig. 5a.
Manchester coding was initially proposed for the ranging signal to limit low frequency interference with the LISA phase measurement  , however the use of Manchester coding has the added benefit of reduced dispersion through the phasemeter. Figure 5b compares the filtered and unfiltered pulse correlation for Rectangular and Manchester pulses against an ideal demodulation code. The Manchester pulse suffers only a small 0.13dB ‘on-time’ signal loss with minimal decay compared to the significant tail evident in the Rectangular pulse correlation, which is verified by the time domain trace in Fig. 5a. The introduced phase delay can be seen in the asymmetric shape of the correlation functions, which will influence the formation of the closed loop timing error signal to be introduced in Section 3.
The analysis to this point has assumed that only two ranging pulses can correlate with one demodulation pulse, so immediately the Rectangular pulse would break this condition due to the large decay. Figure 5b demonstrates that the decay contribution outside (0, TP) for the Manchester pulse shape is small (≪ 1%) compared to other terms, allowing us to simply replace the pulse function with the Manchester pulse fM(t) and auto-correlation RM(τ). The pulse correlation after the phasemeter is now RM(Δτ) ★ hPM = RPM(Δτ) and the demodulation correlation can be written as;
2.3. Interference Contribution
To evaluate the system performance, we can make an assumption that the correlation between uncorrelated or unaligned PRN codes appears as additive white noise [7, 15]. Whilst the repetitive nature of the PRN sequences guarantees that these correlations will be periodic, the independent LISA clocks will disrupt this periodicity. This allows us to approximate the ‘unwanted’ and ‘interfering’ correlations as white noise sources.
The unwanted auto-correlation appears as a noise source C ĉ2,c2 [n, ±1] = ν ĉ2,c2 [±1], with variance . A similar assumption may be made for the interference cross-correlation terms, where the interfering contribution is reduced to two independent noise sources C ĉ2,c1 [n,mi] = ν ĉ2,c1 [mi] and C ĉ2,c1 [mi + 1] = ν ĉ2,c1 [mi + 1], with variance . This allows a different interpretation of A ϕQ,ĉ2 [n] as shown in Eq. (6) below.
Interestingly, Eq. (6) predicts that changes in the demodulation delay 2 will modulate the interference contributions through the pulse auto-correlation. The interference pulse correlation weightings Rf( 2mod TP) and Rf((τ̂ 2 + 1)mod TP) are each dependent upon the delay, acting as a time varying gain to the correlation noise. On short time scales, performance predictions must be used directly Eq. (6), however on longer averaging periods we can simplify the result.
When the demodulation delay is tracking the long terms changes in the pseudo-range, the interference code fluctuations will average over the Manchester pulse auto-correlation to appear as a single noise source ν ĉ2,c1 with zero mean and variance . Similarly, the unwanted noise term will be given as Rf ((Δτ 2 + TP)mod TP) ν ĉ2,c2 [±1] = ν ĉ2,c2 with zero mean and a timing error dependent variance .
Accumulating all the correlation noise into a single noise term νA, with variance , the demodulated correlation A ϕQ,ĉ2 [n] can be written as a timing error dependent random variable given by Eq. (7).
To place this result within the context of LISA, we can consider Eq. (3) with a chip rate of 1 MHz and a correlation period τCorr of N = 50 Chips (50 μs or 20 kHz correlation rate). The modulation depth is β = 0.14 for 1% of the carrier power. For perfect demodulation, the correlation noise terms give a noise power . The shot noise contribution of gives a noise variance of over a 20 kHz bandwidth. This highlights that the demodulation noise is dominated by the interference introduced by the outgoing ranging code, with a noise power > 10 dB larger than shot noise. For perfect demodulation alignment with Δτ 2 = 0, the Signal to Interference Noise ratio (SINR) is 3N/2. The noise models in the presented in this section were verified by simulation.
3. Timing Tracking
Recovery of the pseudo-ranging information requires that the delay of the incident ranging signal τ 2 be determined to within 3 ns (or 1 m range) and is equivalent to demodulating the ranging signal phase to within 10−3 chips. Changes in this delay will be driven by two dominant timing effects; the LISA arm length fluctuations and the relative clock differences between spacecraft. The delay locked loop derives a timing error signal from an ‘early’ and a ‘late’ correlation to track the resulting changes in code arrival time. The early / late demodulation code is nominally advanced/ delayed half a chip from the ‘on-time’ timing point, however the exact separation may be reduced for better sensitivity at the expense of acquisition reliability. Any change in arrival time will add power to either the early or late correlation, indicating the direction of the change. The difference between the correlation forms a timing error signal proportional to the timing offset Δτ 2.
We define the early and late codes as and respectively, with associated correlations and . The timing error signal is dependent upon Δτ 2 and is given by
The correlations and can each be expanded using Eq. (7) with a timing offset of Δτ 2 = ±TP/2 as appropriate. This gives the relation in Eq. (8) for the error signal output as a function of timing error. The phasemeter and interference noise contributions have been grouped into noise sources and respectively. The noise terms and each have a delay dependent variance .
Figure 6 shows the noiseless error signal ε ϕQ,c2 against timing error Δτ 2. The error signal is approximately linear for errors within | Δτ 2| ≤ TP/2, however the error signal zero crossing point occurs at an offset from the ideal timing point Δτ 2 = 0. This is a direct consequence of the delay introduced by the phasemeter and results in an offset of the zero crossing point Δτ 0 which is dependent upon the phasemeter closed loop decay time 1/α by,
For α = 2π × 105, the timing offset is Δτ 0 ≈ 75.2 ns or ≈ 22.6 m with a ∼ 0.82 dB Signal to Noise Ratio (SNR) loss. Importantly, without automatic gain control of the digitized heterodyne beat note, any amplitude deviations will couple into the phasemeter open loop bandwidth fu though gain scaling of the 1/f slope. Consequently the bandwidth fu and the error signal zero crossing point will vary with any amplitude variation. As the effective unity gain frequency scales with amplitude noise, this will introduce in an additional source of time varying, timing offset which must be compensated for. Around the target phasemeter operating amplitude AP, the coupling between amplitude noise ΔAP and timing offset is Δτ 0 ≈ 75.2 + 70ΔAP/AP ns. Allocating 0.03 ns error to this error source requires knowledge or control of the fractional amplitude fluctuation to within ΔAP/AP ≈ 4×10−4. This can either be accomplished by automatic gain control or calibrated in offline post-processing using the to the amplitude information recorded by the phasemeter at a fidelity of ΔAP/AP ≈ 10−6.
3.1. Closed Loop Timing Analysis
With an error signal defined, we can now consider closing the timing control loop to form a timing estimate. LISA specifications require an absolute timing estimate within ≈ 3 ns(or 1 m) for all sample points. After initialising the demodulation delay through the acquisition system, the delay estimate 2 will be updated by the error signal output. Any orbit or clock effects are significantly slower than the ranging system will operate , hence a second order Integral, Double Integral (II 2) controller is selected, which maximises low frequency tracking while minimising the sensitivity to high frequency noise. The closed loop system is modelled to predict the effect of phase and interference noise propagating through the timing control loop and an associated noise floor is derived for the timing estimate 2. A diagram of the system under consideration is show in Fig. 7.
For small timing deviations around the zero crossing point, the error signal is approximately linear and is given by ε ϕQ,c2 (Δτ 2) = βN/τCorr(RPM(Δτ 2 + TP/2) − RPM(Δτ 2 − TP/2)) ≈ 2βN/τCorr Δτ 2. This linear operation requires the acquisition algorithm to accurately identify the demodulation delay to within |Δτ 2| < TP/2 for this analysis to be valid. From Fig. 6, we can see this assumption is only valid when the timing offset from 0 is accounted for. Within the linear region, the error signal from Eq. (8) can be written as;
We define the error signal gain G = ε ϕQ,c2(Δτ 2)/Δτ 2 = 2βN/τCorr and the II 2 controller C II2 (s) =kI/s + (k I2/s)2, with Laplace variable s and controller gains kI = 5 × 10−3 and k I2 = 2.5 × 10−4 selected for a closed loop bandwidth of ≈ 1.4 kHz.
The closed loop transfer function can be calculated from Fig. 6 as:
The interference noise contribution is which converts to a PRN phase noise spectrum of . The equivalent interference noise timing error will be with an equivalent ranging error of 0.7 ns or approximately 0.2 m rms over 0.5 Hz bandwidth. Contributions from the phase measurement and shot noise are at , which has an equivalent timing noise spectrum of and an error of 3.5 × 10−2 ns or ≈ 10 mm rms at 0.5 Hz bandwidth.
Once the 75.2 ns delay has been compensated, the interference limited ranging precision will meet the LISA requirement for 1 m absolute range knowledge.
4. Test bed results
The ranging system was integrated with the LISA phase measurement systems and tested on the JPL TDI test bed, a ‘proof-of-concept’ demonstration for the effectiveness of TDI . The realtime ranging between platforms provides the capacity to further verify TDI with the required LISA signals and processing. The PRN ranging was implemented on a National Instruments 7833 FPGA development platform, enabling rapid prototyping and design verification.
The TDI test bed imitates a collapsed LISA architecture with two independent dummy spacecraft nodes separated by static 1.25 m arm length. The basic experimental setup is shown in Fig. 2, with further details available in . LISA-like signalling is used to gather all measurements required by TDI, successfully demonstrating the suppression of laser frequency noise by many orders of magnitude. Importantly, each dummy spacecraft uses an independent clock source to drive all digitisation, phase measurements, digital signal processing and PRN generation. The frequency offset between the two node clocks used in the testbed nodes has been measured in  and shows a frequency error of ≈ 1 ppm between stations. Each node generates a unique PRN ranging signal, using a 17 bit ‘Maximum Length’ sequence truncated to 128,000 chips, for modulation onto the laser using an Electro-Optic Modulator. Reliable acquisition of the code can be accomplished in ≈ 12.8s by averaging over 50 chips with a TP/2 separation between candidate timing points.
The static arm length of the test bed determines that the pseudo-range measurement will be dominated by the difference between node clocks. For a 1 MChip/s chip rate, the 1 ppm difference between clocks amounts to a slip rate of 1 Chip/s. For a single direction pseudo-range measurement, this will appear as a ∼ 300 m/s change in spacecraft separation, much faster than the maximum ∼ 10 m/s velocity predicted for LISA orbits . This ramp between pseudo-range measurements is clearly visible in Fig. 8a, however because the ramp is antisymmetric between stations it will be cancelled in the round trip range measurement.
In the LISA baseline design, a 6 GHz clock sideband signal is derived from the spacecraft local clock and modulated onto the laser in addition to the ranging signal. The primary use for this sideband signal is for removal of the clock noise contribution to the phase measurement which scales directly with the heterodyne frequency , however the beat note between the GHz sidebands also provides an estimate of the difference between the phase of the clocks they are generated from. Using about 10% of the optical power, the sideband beat note provides a high SNR readout of the clock difference and, due to the static arm lengths in the test bed, can be used to calibrate the performance of the ranging system.
Figure 8b shows this clearly, where the detrended single direction ranging estimate and GHz clock sideband are tracking the same clock deviations. The difference between the two independent measurements, shown in the difference trace, demonstrates that each sample of the ranging estimate, updated at 3.33 Hz, suffers a ≈ 0.65 ns rms error relative to the clock sideband signal when averaged to a 0.5 Hz signal bandwidth. This is equivalent to ≈ 0.19 m rms range error and demonstrates close agreement with the ≈ 0.7 ns or 0.2 m rms error predicted in Section 3.1.
Figure 9 shows the Root Power Spectral Density (RPSD) of the experimental results achieved for the bidirectional ranging estimate (blue) and 6 GHz sideband signals (dark green) which show close agreement at low frequencies. These traces are overlayed onto the white interference (dashed) and shot noise (solid) level predictions from Section 3, with interference noise present at and a shot noise contribution of . The difference between the clock sideband signal and the pseudo-range shows an estimate of the residual ranging noise spectrum (light green). The ranging estimate spectrum closely matches the predicted white interference level, indicating the ranging measurement is limited by interference noise. This is further verified by the single code trace, which represents a single direction ranging measurement (red) with the interfering code deactivated. This trace give a better estimate of the true ranging noise floor and appears to be limited by the known testbed displacement noise limit of .
The interesting feature of the RPSD is the clear cross-over frequency between the clock signal and the interference noise. This indicates that the optimal averaging period for the ranging signal will be ≈ 0.2 Hz, which produces a ≈ 0.38 ns rms error. Changing the averaging bandwidth away from this optimal value will either allow more white interference noise to couple into the measurement or suppress the clock signal, increasing estimation error in both cases. Importantly, this cross-over frequency is clock specific and does not indicate the optimal filter bandwidth for LISA. As such, we have selected a 0.5 Hz bandwidth as the nominal figure of merit as it is close to the corner frequency for the single code measurement (without interference).
The presence of the noise spikes seen at around 1 Hz (and 0.8 Hz) in the ranging psd corresponds to the ≈ 1 Chip/s slip rate. The spike occurs as a consequence of the Manchester coding scheme. In the early and late signal calculation, the intentionally misaligned demodulation of the Manchester code produces a strong residual tone at the incoming chip frequency (≈ 1 MHz ± 1 Hz). After decimation inside the DLL, this tone is is aliased down give an oscillation in the error signal at the 1 Hz chip slip rate. This effect can be mitigated by improved DLL filtering or filtering the ranging output prior to TDI.
5. Data Modulation and Transmission
The binary nature of PRN modulation naturally permits the transmission of data upon the ranging signal without significantly degrading performance. A single data bit may be encoded into the sign of the ranging signal, with each bit represented by one correlation period (50 PRN code chips). To transmit a ‘1’ bit the transmitter intentionally inverts its outgoing ranging signal over the 50 chip interval. This inversion is detected at the receiver as a negative correlation. For a ‘0’ bit, the signal is transmitted uninverted and a positive correlation is detected.
To assist with data packet synchronisation, a frame can be defined using the repetition length of the PRN code as shown in Fig. 10. For this reason, the PRN sequence was truncated to 128,000 code chips (128 ms) for data alignment. Within this frame, we are able to transmit 2,560 bits at 50 chips per bit, exactly meeting the LISA requirement of 20 kbps. The repetition length of the code is a well defined synchronisation event, allowing the frame ‘start bit’ to be readily identified and the data packets correctly reconstructed. An alternate arrangement would involve transmission of a pilot bit pattern, which would erode the data bandwidth available for communications.
Whilst in principle it is possible to select a significantly shorter code (1024 chips) which feature reduced cross-correlation interference when averaged over one code length, the introduction of data transmission with these optimised codes has been shown to degrade the ranging performance . This degradation results from the unknown data applied to the ranging code which destroys the optimised cross-correlation against the interfering code. The use of a significantly longer code sequence acknowledges that this degradation will occur and allows for a longer averaging period of the random cross-correlation fluctuations caused by data transmission. A secondary advantage of the longer code is the reduced ambiguity range introduced by the code repetition.
Since the bit period is equal to the code correlation length, the timing error signal must account for any common sign inversion of the early and late signals resulting from the data. This can be readily accomplished by considering the magnitude of the early and late signals by redefining the error signal as . Within the linear range of the error signal (‖Δτ 2‖ ≪ TP/2), all previous analysis remains applicable.
In this paper we have documented the design, analysis and experimental demonstration of a ranging and optical communication sub-system for LISA. Analytic models for the received signal and noise source were presented, showing that the dominant system noise source results from cross-correlation interference between the incoming and outgoing ranging codes. The system noise sources were shown to lead to a ranging estimate noise floor at approximately and a raw ranging output with ≈ 0.19 m rms error per 3.33 Hz sample with a 0.5 Hz signal bandwidth. This level will successfully meet the LISA requirement of 1 m. Integration of the ranging system in prototype LISA hardware and operation within a LISA-like optical test bed verified the predicted performance levels and enables the use of realistic PRN signalling for future TDI experiments.
This research was supported under Australian Research Council's Discovery Projects funding scheme (project number DP0986003). Part of this research was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA).
References and links
1. M. Tinto and J. W. Armstrong, “Cancellation of laser noise in an unequal-arm interferometer detector of gravitational radiation,” Phys. Rev. D 59(10), 102003 (1999). [CrossRef]
2. M. Tinto, M. Vallisneri, and J. W. Armstrong, “Time-delay interferometric ranging for space-borne gravitationalwave detectors,” Phys. Rev. D , 71(4), 041101 (2005). [CrossRef]
3. LISA Frequency control study team, “LISA frequency control white paper,” ESA document LISA-JPL-TN-823 (2009).
4. D. A. Shaddock, B. Ware, R. E. Spero, and M. Vallisneri“Postprocessed time-delay interferometry for LISA,” Phys. Rev. D 70(8), 081101 (2004). [CrossRef]
5. G. de Vine, B. Ware, K. McKenzie, R. E. Spero, W. M. Klipstein, and D. A. Shaddock, “Experimental demonstration of time-delay interferometry for the laser interferometer space antenna,” Phys. Rev. Lett. 104(21), 211103 (2010). [CrossRef] [PubMed]
6. S. E. Pollack and R. T. Stebbins, “A demonstration of LISA laser communication.”Class. Quantum Grav. 23, 4201 (2006). [CrossRef]
7. E. D. Kaplan, Understanding GPS Principles and Applications, (Prentice Hall PTR, 1996).
8. W. M. Klipstein, R. E. Spero, and D. A. Shaddock, “Anti-aliasing for LISA photoreceiver signals,” JPL Technical Note, (2006)
9. J. J. Esteban, A. F. Garca, J. Eichholz, A. M. Peinado, I. Bykov, G. Heinzel, and K. Danzmann, “Ranging and phase measurement for LISA,” J. Phys.: Conf. Ser. 228, 012045 (2010). [CrossRef]
10. D.A. Shaddock, B. Ware, R.E. Spero, K. McKenzie, G de Vine, D. Robison, T. Stecheson, Y. Chong, C. Woodruff, and W. M. Klipstein, “LISA Phasemeter Technology Assessment and Report,” LISA Project Document LIMAS 2009-002 (2009).
11. D. A. Shaddock, B. Ware, P. Halverson, R. E. Spero, and W. M. Klipstein, “Overview of the LISA phasemeter,” in AIP Conf. Proc.873, pg. 654–660 (2006).
12. Hans-Reiner Schulte “Presentation at LISA Mission Formulation MTR,” (14/15. 4. 2006)
13. Vinzenz Wand “Interferometry at low frequencies: Optical phase measurement for LISA and LISA pathfinder”. Ph.D Thesis (4 2007). Leibniz UniversitätHannover
14. J. G. Proakis and M. Salehi, Communications Systems Engineering, (Prentice Hall, 2002).
15. T. S. Rappaport, Wireless Communications, (Artech House Publishers, 2002).
16. W M Folkner, F Hechler, T H Sweetser, M A Vincent, and P L Bender, “LISA orbit selection and stability,” Class. Quantum Grav. 14, 1405 (1997). [CrossRef]
17. W. Klipstein, P. G. Halverson, R. Peters, R. Cruz, and D. A. Shaddock, “Clock noise removal in LISA,” in AIP Conf. Proc.873, pg. 312–318 (2006).