Range and Velocity Resolution

From Ambiguity to Resolution

The OTFS ambiguity function's main-lobe width directly gives the resolution in range and velocity. This section translates the ambiguity theorem into physical units (meters, m/s) and connects resolution to the system parameters: bandwidth WW sets range, frame duration TT sets velocity.

The point is that OTFS resolution matches the information-theoretic limits: Ξ”R=c/(2W)\Delta R = c/(2W) and Ξ”v=c/(2Tf0)\Delta v = c/(2 T f_0). OFDM-radar achieves the same Ξ”R\Delta R but has effectively infinite Ξ”v\Delta v (cannot resolve velocity at all with a single OFDM symbol). This section quantifies why.

Theorem: Range Resolution: OTFS and OFDM Agree

For any waveform of bandwidth WW, the range resolution (minimum resolvable range separation) is Ξ”Rβ€…β€Š=β€…β€Šc2W.\Delta R \;=\; \frac{c}{2 W}. This is independent of frame duration or modulation format. At W=20W = 20 MHz: Ξ”R=7.5\Delta R = 7.5 m. At W=100W = 100 MHz: Ξ”R=1.5\Delta R = 1.5 m. At W=1W = 1 GHz: Ξ”R=0.15\Delta R = 0.15 m. Both OTFS and OFDM meet this baseline.

Range resolution is determined by how quickly the channel response varies with delay β€” i.e., how wide the ambiguity function is in the Ο„\tau direction. Bandwidth determines the width of the time-domain autocorrelation, which is the ambiguity at Ξ½=0\nu = 0. This is purely a bandwidth property.

For both OTFS and OFDM, the time-domain signal occupies bandwidth WW, so the range resolution is identical. The differences emerge in the Doppler dimension.

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Theorem: Velocity Resolution: OTFS Wins

For OTFS with frame duration TT and carrier f0f_0, the velocity resolution is Ξ”vβ€…β€Š=β€…β€Šc2Tf0.\Delta v \;=\; \frac{c}{2 T f_0}. At T=4T = 4 ms, f0=5f_0 = 5 GHz: Ξ”v=7.5\Delta v = 7.5 m/s. At T=20T = 20 ms, f0=28f_0 = 28 GHz: Ξ”v=0.27\Delta v = 0.27 m/s.

For OFDM (single symbol): velocity resolution is effectively ∞\infty (single-symbol ambiguity is a ridge in Ξ½\nu, no resolution). For OFDM pulse-Doppler (multi-symbol, no precoding): Ξ”v∝c/(2TPRIf0NPRI)\Delta v \propto c/(2 T_{\text{PRI}} f_0 N_{\text{PRI}}) where TPRIT_{\text{PRI}} is the pulse repetition interval and NPRIN_{\text{PRI}} the number of pulses. Achieves the same Doppler resolution as OTFS at the same total dwell time.

The distinction: OTFS achieves the resolution with a single coherent frame and simultaneously carries data. OFDM requires a dedicated radar mode.

Velocity resolution depends on the observation time. OTFS observes the target for duration TT via the Doppler-axis dimension; OFDM observes via TPRIT_{\text{PRI}} over NPRIN_{\text{PRI}} pulses. Both work, but OTFS integrates communication with sensing β€” the frame duration is the communications frame, not a dedicated radar dwell.

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Key Takeaway

Resolution is set by time-bandwidth product, not waveform shape. Ξ”R=c/(2W)\Delta R = c/(2W) and Ξ”v=c/(2Tf0)\Delta v = c/(2 T f_0) are information-theoretic limits. OTFS achieves both limits with a single coherent waveform that also carries data β€” this is the ISAC enabler. OFDM-radar requires a dedicated pulse-Doppler mode to match OTFS's velocity resolution, sacrificing data throughput.

Range-Velocity Resolution Grid

Plot the achievable (Ξ”R,Ξ”v)(\Delta R, \Delta v) pairs as a function of the system's (W,T,f0)(W, T, f_0). Overlay typical deployment scenarios: automotive (pedestrian detection, 7-class vehicle resolution), drone surveillance, aerial UAV tracking. Observe that OTFS's simultaneous (Ξ”R,Ξ”v)(\Delta R, \Delta v) at a given (W,T)(W, T) is the information-theoretic optimum.

Parameters
10
500
4
5

Definition:

Cramer-Rao Lower Bound for Range-Velocity Estimation

The Cramer-Rao lower bound (CRLB) for the variance of range and velocity estimates, assuming a single target with SNR ρ\rho, is ΟƒR2β€…β€Šβ‰₯β€…β€Šc28Ο€2 W2 ρ,Οƒv2β€…β€Šβ‰₯β€…β€Šc28Ο€2 T2 f02 ρ.\sigma_R^2 \;\geq\; \frac{c^2}{8 \pi^2\,W^2\,\rho}, \qquad \sigma_v^2 \;\geq\; \frac{c^2}{8 \pi^2\,T^2\,f_0^{2}\,\rho}. These bound the accuracy (estimation error) achievable from a single observation. For ρ=20\rho = 20 dB (100100), W=20W = 20 MHz, T=4T = 4 ms, f0=5f_0 = 5 GHz: ΟƒRβ‰₯18\sigma_R \geq 18 cm and Οƒvβ‰₯0.024\sigma_v \geq 0.024 m/s.

The CRLB is roughly 1/ρ1/\sqrt{\rho} times the resolution Ξ”R\Delta R: at high SNR, we can estimate the target's position to sub-resolution accuracy.

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Theorem: OTFS Achieves the CRLB

For OTFS with the thumbtack ambiguity function and ML estimation, the variance of the range and velocity estimates matches the CRLB asymptotically at high SNR: ΟƒR2β†’c28Ο€2 W2 ρ,Οƒv2β†’c28Ο€2 T2 f02 ρ.\sigma_R^2 \to \frac{c^2}{8 \pi^2\,W^2\,\rho}, \qquad \sigma_v^2 \to \frac{c^2}{8 \pi^2\,T^2\,f_0^{2}\,\rho}.

The Fisher information of the range-velocity estimation problem is maximized when the ambiguity function is thumbtack-shaped (no directional degeneracy). OTFS's thumbtack achieves this; OFDM's ridge does not (the velocity Fisher information is degenerate along the ridge).

OFDM pulse-Doppler achieves the Doppler CRLB only after coherent integration across pulses β€” requiring dedicated radar mode and more processing steps. OTFS does this with a single coherent frame.

⚠️Engineering Note

Achievable Accuracy in Practice

Practical OTFS radar accuracy at SNR = 20 dB:

  • Range: ΟƒRβ‰ˆ0.2\sigma_R \approx 0.2–0.50.5 m (at W=20W = 20 MHz). Better than 1/10th the range resolution.
  • Velocity: Οƒvβ‰ˆ0.03\sigma_v \approx 0.03–0.10.1 m/s (at T=4T = 4 ms, f0=5f_0 = 5 GHz). Subcentimeter-per-second accuracy.

These are single-observation estimates; averaging multiple frames improves by 1/Nframes1/\sqrt{N_{\text{frames}}}. For automotive ISAC with 100 frames/sec: total estimation error in the 10 cm range and 1 cm/s velocity β€” sufficient for pedestrian detection (1.4 m/s) and vehicle tracking.

For mmWave ISAC at f0=28f_0 = 28 GHz: Οƒv\sigma_v improves by factor 5.6 due to higher carrier. Velocity accuracy enters the sub-mm/s range β€” suitable for gesture recognition, health monitoring, and other fine-motion applications.

Practical Constraints
  • β€’

    ΟƒR∼0.2\sigma_R \sim 0.2 m, Οƒv∼0.03\sigma_v \sim 0.03 m/s at typical SNR

  • β€’

    Multi-frame averaging: 1/N1/\sqrt{N} improvement

  • β€’

    Automotive ISAC target: 0.1 m range, 0.01 m/s velocity