Nonuniform Doppler extraction-enhanced multichannel extensive cancellation algorithm for passive radar using Iridium satellite signals

Abstract

Passive radar (PR) relies on receiving signals reflected from targets by other existing noncooperative radiation sources, which are broadly divided into ground- and space-based categories, to achieve target detection and tracking. In the context of space-based PR, this paper proposes a PR using the Iridium satellite signal, which is a low-orbit satellite communication signal with global coverage. With an improved detection range and accredited ambiguity function, a PR using the Iridium satellite signal can address the issues of limited terrestrial coverage for ground-based PR and insufficient receiving power for medium- to high-orbit space-based PR. In addition, to address the problem of multipath clutter broadening caused by the dual movement of low-orbit satellites and the PR receiver, this paper proposes a nonuniform Doppler extraction-enhanced multichannel extensive cancellation algorithm (NuDE-mECA) to suppress multipath clutter broadening while preserving near-field low-speed target detection capabilities. Compared with the traditional multichannel ECA and uniform Doppler extraction multichannel ECA, the NuDE-mECA achieves significantly reduced computational complexity while improving clutter suppression performance and maintaining detection capabilities for low-speed targets. These results provide valuable insights for the lightweight and high-precision design of space-based PR systems.

Keywords: Detection power analysis; Iridium satellite signal; Multichannel extensive cancellation algorithm; Passive radar.

Fig. 1

Scenario diagram of the PR.

Fig. 2

Flowchart of Iridium PR signal processing.

Fig. 3

Relationships between the maximum detection range and the coherence time and RCS for the PR using the Iridium, Starlink, GPS, and DVB-S signals.

Fig. 4

Iridium user-link TDMA frame structure.

Fig. 5

Iridium physical layer channel frame format.

Fig. 6

STL signal ambiguity function.

Fig. 7

Doppler and delay dimensions of the STL signal ambiguity function: (a) Doppler dimension (velocity); (b) delay dimension (distance).

Fig. 8

Block diagram of the NuDE-mECA.

Fig. 9

Reference matrix column decomposition in the multichannel ECA.

Fig. 10

First Doppler frequency extraction process.

Fig. 11

Reference matrix reconstruction.

Fig. 12

Curve of the variation in the computational complexity of the multichannel ECA with the Doppler suppression range.

Fig. 13

Relative positions of the targets and clutter in four special scenarios: (a) far-field high-speed target; (b) near-field high-speed target; (c) far-field low-speed target; (d) near-field low-speed target.

Fig. 14

Ambiguity function diagram of the time delay dimension after the multichannel ECA is suppressed in four special scenarios: (a) far-field high-speed target; (b) near-field high-speed target; (c) far-field low-speed target; (d) near-field low-speed target.

Fig. 15

Simulation diagram.

Fig. 16

Ambiguity function for the ideal suppression case: (a) front view; (b) delay dimension profile.

Fig. 17

Ambiguity function diagram after suppression by the NuDE-mECA: (a) front view; (b) delay dimension profile.

Fig. 18.

2D-CFAR detection results after suppression by the NuDE-mECA: (a) front view; (b) vertical view.

Fig. 19

Simulation scene.

Fig. 20

Delay dimension of the ambiguity function diagram before suppression.

Fig. 21

Ambiguity function of the delay dimension suppressed by the NuDE-mECA at different threshold values: (a) the threshold is 14 dB; (b) the threshold is 15 dB; (c) the threshold is 16 dB; (d) the threshold is 17 dB; (e) the threshold is 18 dB; (f) the threshold is 19 dB; (g) the threshold is 20 dB; (h) the threshold is 21 dB.

Fig. 22

Suppression effect of NuDE-mECA with different detection thresholds.