Space is becoming increasingly congested and contested, which calls for effective means to conduct effective monitoring of high-value space assets, especially in Space Situational Awareness (SSA) missions, while there are imperfections in existing methods and corresponding algorithms. To overcome such a problem, this letter proposes an algorithm for accurate Connected Element Interferometry (CEI) in SSA based on more interpolation information and iterations. Simulation results show that: (i) after iterations, the estimated asymptotic variance of the proposed method can basically achieve uniform convergence, and the ratio of it to ACRB is 1.00235 in δ0 ∈ [-0.5, 0.5], which is closer to 1 than the current best AM algorithms; (ii) In the interval of SNR ∈ [-14dB, 0dB], the estimation error of the proposed algorithm decreases significantly, which is basically comparable to CRLB (maintains at 1.236 times). The research of this letter could play a significant role in effective monitoring and high-precision tracking and measurement with significant space targets during futuristic SSA missions.

Precession angle and precession period are significant parameters for identifying space micro-motion targets. To implement high-accuracy estimation of precession parameters without any prior knowledge about structure parameters of the target, a parameters extraction method based on HRRP sequences is proposed. The precession model of cone-shaped targets is established and analyzed firstly. Then the projection position of scattering centers on HRRP induced by precession is indicated to be approximate sinusoidal migration. Sequences of scattering centers are associated by sinusoid extraction algorithm. Precession angle and precession period are estimated utilizing error function optimization at last. Simulation results under various SNR levels based on electromagnetic calculation data demonstrate validity of the proposed method.