Abstract: ‍ ‍The pseudorandom code phase modulated radar has the advantages of covering a larger region， higher measuring accuracy， and stronger anti-interference ability， making it increasingly important in the field of space target detection. This paper proposes a precise parameter estimation method for a far-field， maneuvering target based on the parameter tracking loop. First， the proposed method acquires the initial estimate of the Doppler frequency via fractional Fourier transform， and a coherent carrier extraction loop， which is insensitive to the pseudorandom code modulation， is developed to robustly and accurately track the carrier of the pseudorandom code phase modulated signal. Thus， the velocity of a target can be estimated with high precision. Subsequently， using the relationship between the carrier Doppler frequency and the pseudorandom code Doppler frequency， the local transmit signal is “modified” and the code phase drift is eliminated. Upon obtaining the initial estimation of the pseudorandom code phase based on the autocorrelation characteristics of the pseudorandom code， a carrier-aided coherent code tracking loop is constructed to accurately track the pseudorandom code phases of the maneuvering target and accurately estimate the target range. The proposed method effectively resolves the loss of integration efficiency and deterioration of detection performance induced by autocorrelation-loss， code phase drift， and Doppler spread of the maneuvering target， thus greatly improving parameter estimation accuracy. Compared with partial correlation-fractional Fourier transform， generalized radon-Fourier transform， and the iterative adjacent cross correlation function， the proposed method transforms the traditional multi-dimensional parameter searching problem for the maneuvering target into two successive one-dimensional parameter extraction problems. Consequently， the proposed method significantly reduces the computational cost and decreases the computation time on the premise of obtaining high-precision estimations of the target parameters， making real-time implementation easier. Moreover， the proposed method provides a feasible way to realize autonomous detection and perception under the strong constraints of spacecraft space platform resources.