Subspace smearing and interference mitigation with array radio telescopes

Abstract

Active Radio Frequency Interference (RFI) mitigation becomes a necessity for radio astronomy. The solution commonly applied by the community consists in monitoring the statistics of the received signal, and flag out the detected corrupted data. Subspace projection with array radio telescopes has been suggested as an alternative to data excision to avoid important losses of data and overcome its inherent ineffectiveness with continuous interference.Spatial filtering relies on the estimation of the RFI spatial contribution, and the projection of the subspace spanned by the RFI out of the observed data vector space. To perform well, the dimensionality of the RFI subspace is constrained.RFI subspace estimation techniques assume the source of RFI to be spatially stationary over the sample covariance matrix evaluation. When the relative movement between the telescope and the interferer becomes significant, the RFI subspace gets smeared over the whole data vector space. The subspace projection can then no longer be applied without affecting the source of interest recovery. This paper addresses the effect of RFI subspace smearing on the subspace projection approach, and suggests an alternative technique based on a covariance matrix subtraction, improving the performance of spatial filtering in the case of high subspace smearing.

Interference mitigation with a modified ASKAP phased array feed on the 64m parkes radio telescope

“…Error in estimating the RFI subspace also limits suppression. Performance can be improved by using reference antennas tracking RFI sources to more accurately estimate their subspace [11], reducing ACM integration time to reduce subspace smearing [9] caused by relative motion between RFI sources and the telescope, and by increasing beam weight update rates so that the mitigation is still valid when applied.…”

Low-Complexity Algorithm for Radio Astronomy Observation Data Transport in an Integrated NGSO Satellite Communication and Radio Astronomy System

“…Thus, the choice between the proposed approach 1 and 2 would depend on the priority of the average cost versus maximum cost in the RAO data transport. Also, by referring to (16) and ( 13) it can be shown that both our two proposed approaches will have the same running computational complexity. However, both of them show a huge enhancement compared to the approach in [1] as illustrated in Fig.…”

A Spectrum Sharing Paradigm for GSO Satellite System and Radio Astronomy System

“…Hence, the RFI at the telescopes will not increase if we allow SCS to use almost all of the idle RAS bands for its downlink transmission. Then, the total bandwidth which can be used by SCS can be B SCS,used = L l=1 N sub,l • B sub,l = 3288 MHz in scenario 2 10 and B SCS,used = 3177 MHz in scenario 3. On the other hand, in scenarios 1, 4, and 5, a larger B SCS,0 causes a larger average unwanted emission power, and hence a trade-off should be made between the total bandwidth of the SCS and the average unwanted power.…”

“…Naturally, we can form an average ratio vector r group with the mth element r group (m). To fairly assign the subband groups to the satellite groups, the assignment problem can be 10 In scenario 2 specifically, if we allow SCS to have B SCS,used = 3250 MHz, the average unwanted emission power is around -45 dBW which remains the same for smaller B SCS,used (as shown in Fig. 16).…”

“…Thus, RFI mitigation plays a more critical role. The existing RFI mitigation methods include digital filtering and sub-space filtering [7]- [10], spatial filtering with array instruments [11]- [17], auxiliary antenna based RFI removal [18]- [21], cognitive radio based approaches [22]- [24], and time-division spectrum sharing [25]- [29]. However, due to the relative locations of the ground telescopes and the satellites, the signals from the satellites may directly hit the dish surface of the telescope and consequently cause strong RFI to the RAS.…”