Pulse compression, usually achieved using a matched filter (MF), is extensively applied in radar/sonar systems. This process improves the signal-to-noise ratio (SNR) of the received signal without increasing the peak transmitted power. However, it is often desirable to accept a slight penalty in the target SNR in order to suppress the range sidelobes. In this paper, a novel weighted mismatched filter (WMMF) that can reduce range sidelobes to the designed level over specified regions is proposed. Two algorithms are provided to calculate the WMMF in different situations. A novel performance metric, the mean sidelobe level over a specified region (MSLSR), is also proposed to demonstrate the performance of the proposed method. Then, the SNR loss is deduced and analyzed based on several experiments. Finally, simulations and experiments based on real measured data are conducted to illustrate the effectiveness of this method. The theoretical evaluation and experiments show that the proposed WMMF can be used for all types of waveforms based on pulse compression processing and can flexibly and effectively suppress range sidelobes. Moreover, the mainlobe and the SNR loss can also be controlled by the proposed algorithms. In addition, this method can be easily applied to existing radar systems without modifying the radar transmitter or receiver.

Pulse-Doppler radar systems with medium/high pulse repetition frequencies (PRFs) usually produce severe range ambiguities, and strong nearby ground/sea clutter will then fold into a single range interval with weak remote target echoes, further limiting the dynamic range of radar. The existing methods for modeling or estimating clutter spectra are usually not applicable to the case of folded clutter. In recent years, pulse-agile waveforms have attracted an increasing amount of attention for resolving range ambiguities. However, cross-correlations among pulse-agile waveforms with the same frequency band, usually required for pulse-Doppler radar to coherently measure the Doppler shift, are not satisfactory for suppressing folded clutter since clutter echoes are much stronger than those of targets. In this paper, two algorithms based on the method of alternating projection (MAP) in the range-Doppler domain (RD-MAP) and the space-Doppler domain (SD-MAP) are proposed to suppress folded clutter and resolve range ambiguities for pulse-Doppler radar based on different types of pulse-agile waveforms. The effectiveness of these algorithms is verified based on several realistic simulations and a ground-based experiment. Iterative solutions and closed-form solutions are both provided for different computational complexity and accuracy requirements in certain application scenarios. Moreover, algorithm analysis, including algorithm boundary analysis, signal-to-noise ratio (SNR) loss, computational complexity and factor selection, is performed to provide an estimation of the applicable conditions and assess the performance of the proposed algorithms.

Finding codes for the desired autocorrelation function (ACF) based on phase-coded modulation waveforms has always been a popular research topic, and the relevant literature is abundant. However, the optimized ACF may not be obtained in band-limited hardware due to the extended spectral sidelobes generated by instantaneous phase changes. Polyphase-coded FM (PCFM) waveforms based on continuous phase modulation (CPM), which uses a shape filter to smooth phase jumps, can provide effective spectral containment. However, for PCFM waveforms using the existing optimized phase codes, the original desired property of the ACF, e.g., a low integrated sidelobe level (ISL) or weighted ISL (WISL), will not be obtained because of the smoothness among all phases. Hence, PCFM waveforms based on CPM should be redesigned and optimized. Moreover, designing pulse-agile waveforms with different phase codes to mitigate range ambiguity has also attracted increased attention in recent years. However, different waveforms will yield range sidelobe modulation (RSM) in Doppler processing, which degrades the attendant Doppler coherency, leading to high sidelobes in the Doppler dimension. In this article, optimization algorithms for designing diverse PCFM waveforms and relevant joint mismatched filters (JMMFs) are proposed. A CPM-based cyclic algorithm (CPM-CA) using the method of alternating projection for optimizing the PCFM waveform with a desired ACF is proposed in the first step. The design of multiple diverse PCFM waveforms with similar ACFs and a small RSM effect is also considered. Then, to further optimize the ISL/WISL and reduce the RSM effect, a novel method for designing JMMFs using a cyclic algorithm (JMMF-CA) is proposed. Simulations and an experiment based on a real radar system indicate that the optimized PCFM waveforms and JMMFs using CPM-CA and JMMF-CA can yield a desired ISL/WISL while achieving a small RSM effect with a low loss of signal-to-noise ratio and satisfactory Doppler robustness.

In the field of sensor signal processing, windows are time-/frequency-domain weighting functions that are widely applied to reduce the well-known Gibbs oscillations. Conventional methods generally control the spectral characteristics of windows by adjusting several of the parameters of closed-form expressions. Designers must make trade-offs among the mainlobe width (MW), the peak sidelobe level (PSL), and sometimes the sidelobe fall-off rate (SLFOR) of windows by carefully adjusting these parameters. Generally, not all sidelobes need to be suppressed in specified applications. In this paper, a novel method, i.e., the inverse of the shaped output using the cyclic algorithm (ISO-CA), for designing window functions with flexible spectral characteristics is proposed. Simulations are conducted to test the effectiveness, flexibility and versatility of the method. Some experiments based on real measured data are also presented to demonstrate the practicability. The results show that the window functions generated using the cyclic algorithm (CA) yield better performance overall than the windows of conventional methods, achieving a narrower MW, a lower PSL, and a controllable SLFOR. In addition, steerable sidelobes over specified regions can be acquired both easily and flexibly while maintaining the original properties of the initial window as much as possible.

An improved CLEAN algorithm for inverse synthetic aperture radar (ISAR) image processing is presented. An adaptive threshold is given to detect real targets after preprocessing by the CLEAN method. The cross-range resolution is emphasized. The results of processing are quite good.