On detection of moving weak targets using MIMO continuous active sonar and Doppler filtering
In this paper, we propose a moving weak target detection method of utilizing multiple-input multiple-output continuous active sonar (MIMO-CAS) and Doppler filtering. We begin by designing frequency diversity continuous wave (FDCW) pulse signals that have very low cross-correlation coefficients. The number of FDCW pulses is equal to the product of the number of transmitting transducers and the number of detection cycles. Secondly, we transmit these FDCW pulses using MIMO-CAS over multiple cycles with a small periodic interval, projecting a large amount of sound energy into the ocean channel. The energy transmitted by MIMO-CAS is sufficient for detecting weak targets using the energy accumulation method. Next, we process the echoes from the moving target with different Doppler shifts using Doppler filters. For each FDCW pulse, we design a bank of Doppler filters based on the waveform and discrete Doppler shifts of the FDCW pulse. Finally, the Doppler-filtered outputs are accumulated coherently or incoherently in the range Doppler domain. And the high-gain accumulated output is outputted. MIMO-CAS makes full use of the Doppler filtering abilities of the FDCW pulses to suppress the reverberation near-zero Doppler shifts, and simultaneously utilizes the multi-cycle accumulation to suppress noise. Via numerical simulations, we show that MIMO-CAS can improve the detection performance of the weak targets.
Authors
- Yixin Yang (ORCID: https://orcid.org/0000-0003-4817-9911)
- Xionghou Liu (ORCID: https://orcid.org/0000-0001-6736-6873)
- Jie Wang (ORCID: https://orcid.org/0000-0002-1489-7184)
- Chao Sun (ORCID: https://orcid.org/0000-0003-4404-9183)
Institutions
- Northwestern Polytechnical University (CN)
- Zhanjiang Experimental Station (CN)
- Shaanxi University of Science and Technology (CN)
Publication Details
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1117/12.3061877
- Primary Topic
- Target Tracking and Data Fusion in Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00