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 sets range, frame duration sets velocity.
The point is that OTFS resolution matches the information-theoretic limits: and . OFDM-radar achieves the same but has effectively infinite (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 , the range resolution (minimum resolvable range separation) is This is independent of frame duration or modulation format. At MHz: m. At MHz: m. At GHz: 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 direction. Bandwidth determines the width of the time-domain autocorrelation, which is the ambiguity at . This is purely a bandwidth property.
For both OTFS and OFDM, the time-domain signal occupies bandwidth , so the range resolution is identical. The differences emerge in the Doppler dimension.
Autocorrelation width
For a pulse with bandwidth , the autocorrelation has first null at .
Two-way radar
Target at range : round-trip delay . Two targets resolved if , i.e., .
Theorem: Velocity Resolution: OTFS Wins
For OTFS with frame duration and carrier , the velocity resolution is At ms, GHz: m/s. At ms, GHz: m/s.
For OFDM (single symbol): velocity resolution is effectively (single-symbol ambiguity is a ridge in , no resolution). For OFDM pulse-Doppler (multi-symbol, no precoding): where is the pulse repetition interval and 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 via the Doppler-axis dimension; OFDM observes via over pulses. Both work, but OTFS integrates communication with sensing β the frame duration is the communications frame, not a dedicated radar dwell.
OTFS Doppler resolution
From the ambiguity theorem: first null in at . Velocity resolution: .
OFDM single symbol
Single OFDM symbol duration . Doppler resolution: . At kHz: kHz. Velocity resolution: . At GHz: m/s. Useless.
OFDM pulse-Doppler
pulses at interval . Doppler resolution: . For typical s: Hz. At 5 GHz: m/s. Worse than OTFS with same dwell ( ms): Hz β same!
Conclusion
Given the same time-bandwidth product, OTFS and OFDM-pulse- Doppler achieve the same Doppler resolution. The difference is that OTFS does this while carrying data, enabling ISAC. OFDM-pulse-Doppler requires a dedicated radar waveform with no data capacity.
Key Takeaway
Resolution is set by time-bandwidth product, not waveform shape. and 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 pairs as a function of the system's . Overlay typical deployment scenarios: automotive (pedestrian detection, 7-class vehicle resolution), drone surveillance, aerial UAV tracking. Observe that OTFS's simultaneous at a given is the information-theoretic optimum.
Parameters
Definition: Cramer-Rao Lower Bound for Range-Velocity Estimation
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 , is These bound the accuracy (estimation error) achievable from a single observation. For dB (), MHz, ms, GHz: cm and m/s.
The CRLB is roughly times the resolution : at high SNR, we can estimate the target's position to sub-resolution accuracy.
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:
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.
Fisher information matrix
For a single-target observation in noise:
OTFS's thumbtack
OTFS ambiguity is separable: . Fisher matrix is diagonal: . Diagonal entries: , .
CRLB
. . Translate to range and velocity via and : the claimed CRLB.
Achievable Accuracy in Practice
Practical OTFS radar accuracy at SNR = 20 dB:
- Range: β m (at MHz). Better than 1/10th the range resolution.
- Velocity: β m/s (at ms, GHz). Subcentimeter-per-second accuracy.
These are single-observation estimates; averaging multiple frames improves by . 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 GHz: 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.
- β’
m, m/s at typical SNR
- β’
Multi-frame averaging: improvement
- β’
Automotive ISAC target: 0.1 m range, 0.01 m/s velocity