A Long-Time Coherent Integration Method for Hypersonic Target Echoes With Velocity-Induced Scaling

In hypersonic target detection scenarios involving large time– bandwidth product signals, the scale effect of target echo pulses leads to severe mismatch in conventional pulse compression filters. To address this issue, an efficient method for pulse compression and inter-pulse coherent integration, termed the Improved Radon Inverse Fourier Transform (IRIFT), is proposed. The IRIFT algorithm improves upon the Modified Radon Inverse Fourier Transform (MRIFT) in two key aspects. First, it replaces the compensation function in MRIFT with truncated sinc interpolation for velocity searching and sample collection, effectively eliminating the signal-to-noise ratio (SNR) loss and parasitic harmonic interference introduced by the compensation function. Second, following velocity search in the two-dimensional frequency domain, IRIFT performs range pulse compression using filters matched to the corresponding velocity bins, enabling ideal compression of echoes from hypersonic targets. The range– Doppler spectrum with well-focused echoes is then obtained via inverse FFT along the range dimension. A complete mathematical formulation of the radar echo model and the proposed algorithm is presented within a digital signal processing framework. The analysis quantifies the range and velocity estimation biases induced by conventional methods that neglect intrapulse scale effects, and derives the theoretical upper bound of output SNR gain under ideal matched filtering and coherent integration. Extension to hypersonic targets with constant acceleration is also included. Simulation results demonstrate that the proposed algorithm achieves near-optimal performance in both detection and parameter estimation for single and multiple targets.