Simulation and Experimental Validation of a Combined Ion Line and Plasma Line Inversion Method for Incoherent Scatter Radar
doi: 10.11728/cjss2026.05.2026-0006 cstr: 32142.14.cjss.2026-0006
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Abstract: In the ionospheric monitoring, one of the key techniques is the Incoherent Scatter Radar (ISR), which usually uses the so called ion line spectra resulted from the ion acoustic wave to derive multiple plasma parameters including electron density, electron and ion temperature, and ion velocity and composition. In addition to the ion line, ISR could also measure the so called plasma line spectra due to the existence of Langmuir wave, the dispersion relation of which is associated with the electron density and temperature. In the conventional ion line inversions, the Temperature-Ion Composition Ambiguity (TICA) and the systematic bias hinder the accuracy of retrieved parameters. To address these issues, here we propose an improved method by incorporating the information of plasma line into the ion line fitting process. We expect that the retrieval accuracy could be enhanced with the independent constraint on electron density and electron temperature obtained from the plasma line. Simulations based on the International Reference Ionosphere demonstrate that the combined ion line-plasma line method significantly reduces deviations in electron density and temperature, and it can improve the impact of the TICA effect to a certain extent. The comparison of the experimental results of Sanya Incoherent Scatter Radar with the ionosonde data on 6 June 2022 shows that this method has a certain effect on improving the electron density. This study establishes the feasibility of combined inversion for ISR data analysis, enabling more accurate and calibration-free ionospheric parameter retrievals in the future.
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Key words:
- Incoherent Scatter Radar (ISR) /
- Plasma line /
- Combined inversion /
- Ion line inversion
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Figure 1. Local Time (LT) and altitude variations of electron density (a), electron temperature (b), ion temperature (c) and oxygen ion ratio (d) used in the simulation calculated by the IRI model
Figure 2. Simulated ACF amplitude versus lag number for five selected altitudes(a) and plasma line frequency offset for the whole profile in the simulation (b) at 11:45 LT
Figure 3. Retrieved results in the simulation. From the left to the right are for four cases listed in Table 1 and from the top to the bottom are results of electron density, electron temperature, ion temperature, oxygen ion ratio and residuals
Figure 4. Relative deviations of the retrieved results from that of the simulated truth (Explanation same as Figure 3)
Figure 5. (a) Altitude variation of measured ion line power spectra by SYISR on 6 June 2022 morning at 09:30 LT. (b) The simultaneous plasma line frequency offset spectrum corresponding to (a), the zero frequency of the spectrum corresponds to the radar transmitting frequency (440 MHz), and the red line is the plasma line extracted after Gaussian fitting
Figure 6. Comparison between the traditional ion line inversion (blue dotted line) and combined plasma/ion line inversion (red dotted line) for electron density (a), electron temperature (b), and ion temperature (c) for realistic SYISR measurements at 09:30 LT on 6 June 2022. Also embedded in (a) is the electron density profile measured by a co-located ionosonde
Figure 7. Deviation of electron density measured by different inversion methods from 07:00 LT to 11:00 LT to ionosonde
Table 1. Parameter configuration of the simulation experiments
Fitting setup Initial guessed deviation/(%) SNR of ion line /dB SNR of plasma line /dB Case 1 Ion line fitting 10 13 ― Case 2 $ {N}_{\text{e}} $ used as priori 10 13 9 Case 3 $ {T}_{\text{e}} $ used as priori 10 13 9 Case 4 Combined ion line/plasma line 10 13 9 
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