Reject wrong-sized MEM-RBPF control inputs

[FlorianPfaff]

Summary

• validate MEMRBPFTracker.predict_linear() control inputs against the kinematic-state shape
• reject broadcastable but wrong-sized arrays before mutating tracker configuration or state
• reuse the validated control vector during prediction
• add a focused NumPy regression covering the no-mutation guarantee

Root cause

predict_linear() previously converted inputs only at the point of addition. NumPy therefore accepted shapes such as (1,) and broadcast the single value across every component of a four-dimensional kinematic state, silently applying an unintended control.

Fix

Convert and validate inputs at the start of prediction. A non-None control must have exactly the same shape as kinematic_state; otherwise the method raises ValueError before changing the system matrix, process noise, kinematic state, covariance, or conditional extent state.

Validation

• reconstructed the source from the current GitHub blob and verified the unmodified reconstruction matched blob fec88b01d0c9be7486b13bc3f3710301d4c5b9bd byte-for-byte
• python -m py_compile passes for the modified module and regression test
• the exact regression passes in a minimal NumPy-backed harness
• branch comparison: 8 source additions, 1 source deletion, and one 56-line regression file

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	23.35s
✅ JSON	prettier	7	0	0	0	1.21s
✅ JSON	v8r	7		0	0	5.86s
✅ MARKDOWN	markdownlint	68	0	0	0	2.29s
✅ MARKDOWN	markdown-table-formatter	68	0	0	0	1.12s
✅ PYTHON	black	1543	197	0	0	103.16s
✅ PYTHON	isort	1543	367	0	0	2.81s
✅ REPOSITORY	betterleaks	yes		no	no	1.96s
✅ REPOSITORY	checkov	yes		no	no	59.4s
✅ REPOSITORY	gitleaks	yes		no	no	15.54s
✅ REPOSITORY	git_diff	yes		no	no	0.4s
✅ REPOSITORY	secretlint	yes		no	no	75.55s
✅ REPOSITORY	syft	yes		no	no	4.66s
✅ REPOSITORY	trivy-sbom	yes		no	no	5.93s
✅ REPOSITORY	trufflehog	yes		no	no	33.55s
✅ YAML	prettier	11	0	0	0	0.71s
✅ YAML	v8r	11		0	0	12.7s
✅ YAML	yamllint	11		0	0	0.6s

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