Ant-Mutated Immune Particle Filter Design for Terrain Referenced Navigation with Interferometric Radar Altimeter

Round 1

Reviewer 1 Report

 

1. This paper introduces an ant-mutated immune particle filter for terrain referenced navigation with interferometric radar altimeter. The design is innovative and has good practical significance.
2. The paper is written well, but not up to the publication standard. There are many typos and grammar deficiencies. It is recommended for the authors to proofread and edit the paper. Some examples for improvement are listed here: in Line 59, “crucial impacting” should be “crucially”; Line 62, “to solving” should be “to solve”; Line 111, “the IAPF operate” should be “operates”; Lines 115 and 118, “section 2” should be “Section”; Line 148 “slang range” should be “slant range”; Line 303, “the heuristic value act as” should be “acts as”; Line 304, “filed” should be “fields”; Line 319, “to obtaining” should be “to obtain”; etc.
3. In Line 80, please specify what’s the “second method”. Line 81, please reword “either since”.
4. In Equation 11, row 2, delete “??∗(? + 1) =”
5. Equation 13, s is not shown completely.
6. Line 641, please define “CEP”
7. The longitude and latitude errors are compared, how about the error in the DEM heights?
8. The RMS in Fig. 9 is for what measurement: longitude, latitude or DEM height?

Author Response

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Reviewer 2 Report

Overall, this is a nice work on evolved, evolutionary-based, PF design for the case of SAR. Still, before publication, it is my opinion that the following major comments should be addressed before publication:

1)    Please add a notation paragraph at the end of Sec. 1.

2)    Due to the large number of acronyms involved, it would be useful collecting all them in a corresponding table.

3)    In Sec. I the authors discuss EKF and UKF approaches as possible alternatives to the considered PF-based class of filtering algorithms. However, the former are not included in the numerical comparison.

4)    The authors use ACO-inspired variants and evolutions of the well-known PF. I would like them to better motivate the ACO choice as opposed to other evolutionary algorithms, e.g. PSO:

"Multibit decentralized detection through fusing smart and dumb sensors based on Rao test." IEEE Transactions on Aerospace and Electronic Systems 56.2 (2019): 1391-1405.

"Target tracking by sequential random draft particle swarm optimization algorithm." 2018 IEEE International Smart Cities Conference (ISC2). IEEE, 2018.

5)    I would like the authors to discuss the computational complexity involved (in terms of the well-known big O notation) in the considered AMIPF algorithm.

6)    Sec. 5.1 – Please collect all the numerical parameters concurring to describe the considered simulation setup in a corresponding table for reader’s convenience.

7)    Conclusion section should be enriched with a paragraph describing future directions of research. One extension may be investigating if tracking by-products could be used to infer the position of the radar, following e.g.:

"Tracking the tracker from its passive sonar ML-PDA estimates." IEEE Transactions on Aerospace and Electronic Systems 50.1 (2014): 573-590.

Author Response

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Round 2

Reviewer 2 Report

Overall, this is a nice work on evolved, evolutionary-based, PF design for the case of SAR.

The authors have satisfactorily addressed my previous comments and modified their manuscript accordingly. Hence, I am glad to recommend the present work for publication.

Please double-check the whole bibliography for typos, e.g. [20].

Author Response

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