Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Multistatic Radar Performance in the Presence of Distributed Wireless Synchronization

Kumar Sai Bondada, Daniel J. Jakubisin, R. Michael Buehrer

TL;DR

This work analyzes multistatic radar performance under GPS-independent distributed wireless synchronization using a leader–follower topology. A Bayesian Cramér–Rao bound (BCRLB) framework quantifies how residual frequency and timing offsets propagate into delay and Doppler estimation errors and, consequently, target position and velocity errors. The method combines a TTW-based frequency synchronization and a BDW-based time synchronization scheme, incorporating priors on residual offsets and deriving an equivalent Bayesian information matrix to bound estimation errors. Simulations show that improving synchronization-link quality and bandwidth brings MSR performance close to the ideal case and that the MSR configuration can surpass monostatic performance under favorable link conditions, with practical implementation feasibility suggested by the results.

Abstract

This paper proposes a multistatic radar (MSR) system utilizing a distributed wireless synchronization protocol. The wireless synchronization protocol uses a two-tone waveform exchange for frequency synchronization and a bi-directional waveform exchange for time synchronization, independent of GPS. A Bayesian Cramer-Rao lower bound (BCRLB) framework is developed to quantify the impact of synchronization offsets on joint delay and Doppler estimation, and consequently, on target localization and velocity estimation accuracy. Simulation results derived from the analytical expressions establish the extent to which the residual synchronization offsets degrade the MSR's performance. The performance of the synchronization links primarily depends on the synchronization-link channel and transmit parameters; optimizing these parameters enables the MSR configuration to surpass the monostatic performance and approach the ideal case. Furthermore, the simulated synchronization-link parameters suggest that practical implementation is feasible.

Multistatic Radar Performance in the Presence of Distributed Wireless Synchronization

TL;DR

This work analyzes multistatic radar performance under GPS-independent distributed wireless synchronization using a leader–follower topology. A Bayesian Cramér–Rao bound (BCRLB) framework quantifies how residual frequency and timing offsets propagate into delay and Doppler estimation errors and, consequently, target position and velocity errors. The method combines a TTW-based frequency synchronization and a BDW-based time synchronization scheme, incorporating priors on residual offsets and deriving an equivalent Bayesian information matrix to bound estimation errors. Simulations show that improving synchronization-link quality and bandwidth brings MSR performance close to the ideal case and that the MSR configuration can surpass monostatic performance under favorable link conditions, with practical implementation feasibility suggested by the results.

Abstract

This paper proposes a multistatic radar (MSR) system utilizing a distributed wireless synchronization protocol. The wireless synchronization protocol uses a two-tone waveform exchange for frequency synchronization and a bi-directional waveform exchange for time synchronization, independent of GPS. A Bayesian Cramer-Rao lower bound (BCRLB) framework is developed to quantify the impact of synchronization offsets on joint delay and Doppler estimation, and consequently, on target localization and velocity estimation accuracy. Simulation results derived from the analytical expressions establish the extent to which the residual synchronization offsets degrade the MSR's performance. The performance of the synchronization links primarily depends on the synchronization-link channel and transmit parameters; optimizing these parameters enables the MSR configuration to surpass the monostatic performance and approach the ideal case. Furthermore, the simulated synchronization-link parameters suggest that practical implementation is feasible.
Paper Structure (17 sections, 24 equations, 4 figures, 3 tables)

This paper contains 17 sections, 24 equations, 4 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Signal Model with Synchronization Offsets
  3. BCRLB for Delay $\tau$ and Doppler $f_d$
  4. BCRLB for Delay $\tau_i$ and Doppler $f_i$
  5. Fisher Information
  6. Partial Derivatives of the Mean
  7. Full FIM with Nuisance Parameters
  8. Adding Gaussian Priors for Offsets
  9. Equivalent BIM for $\tau_if_i^\top$
  10. Bayesian CRLB
  11. CRLB for Position $\mathbf{x}$ and Velocity $\mathbf{v}$
  12. Partial Derivatives of the Mean
  13. Distributed Wireless Synchronization
  14. Frequency Synchronization
  15. Time Synchronization
  16. ...and 2 more sections

Figures (4)

  • Figure 1: Multistatic radar system illustrating a leader radar and multiple follower radars.
  • Figure 2: Two-dimensional layout of the leader and follower radars.
  • Figure 3: Time and frequency synchronization performance: (a) bidirectional waveform exchange for clock alignment and (b) two-tone waveform broadcasting for frequency alignment.
  • Figure 4: Multistatic radar performance under ideal conditions (no synchronization offsets) and with synchronization offsets.