Radar Development Framework

0.6.1

Implement Target Filtering Modes for LiDAR and Radar Systems

- Introduced the ETraceTargetMode enumeration to define target filtering options: Terrain Only, All (Terrain + Entities), and Entities Only.

- Updated RDF_LidarSettings and RDF_RadarSettings to use the new target filtering modes, which affects ray casting behavior.

- Enhanced RDF_LidarDemoConfig to include target filtering mode configuration.

- Modified the demo script to support setting and validating target filtering modes during initialization.

- Updated documentation to reflect the changes to target filtering mode functionality and its impact on scan behavior.

0.6.0

📡 Radar Development Framework — Update Log

Update Date: 2026-02-20

🆕 New Features

Electromagnetic Wave Radar System (First Full Release)

Complete Physical Simulation Pipeline: FSPL Propagation Loss, Atmospheric Attenuation, Rain Attenuation, Radar Equation (SNR), RCS Target Cross-Section Model

Doppler Frequency Shift Processing + MTI Moving Target Indication (Filtering Stationary Clutter)

CA-CFAR / OS-CFAR Constant False Alarm Rate Detection (Built-in Offline Lookup Table, Automatic Loading)

4 Operating Modes: Pulse / Continuous Wave (CW) / Frequency Modulated Continuous Wave (FMCW) / Phased Array

On-chip PPI Scanning Circle HUD (Pure Script CanvasWidget, Green Theme)

Target Classification System: Entity Pre-classification (Structure Hierarchy / Name Heuristic) + Target Classifier

SAR Synthetic Aperture Radar Processor (Aperture Accumulation)

ECM Electronic Countermeasures Jamming Model

PPI Display / A-Scope Range Amplitude Map / World Pillar Markers / ASCII Console Map

Complete Demo System (AutoRunner / Demo Cycler / StatsHandler)

EM Voxel Field System (Phase 1–5 Complete)

3D Electromagnetic Field Simulation Voxel Mesh, Supports Signal Descriptor and Pulse Feature Recording/Estimation

Passive Sensor (Listening to Signals in the Field)

Multi-user Network Synchronization (Server Authority)

Debugging Visualization

LiDAR HUD (New)

On-chip PPI Scan HUD (Blue Theme), can be used independently or connected to AutoRunner for automatic refresh

✨ Improvements

LiDAR

New public static APIs for HUD: IsVisible() / FeedSamples() / AttachToAutoRunner() / DetachFromAutoRunner(), supporting direct HUD driving outside the Demo system

New Networked LiDAR Configuration Example (RDF_LidarNetworkSetupExample)

Scan Sampling Extension: Rayshots now carry entity references and surface materials Information

Sweep Strategy Improvement: Highly uniform distribution, eliminating clustering.

AutoRunner Memory Optimization: Proactively releases shape and sample references to prevent leakage during long-term operation.

Radar HUD

Synchronously added 4 public static APIs, with interfaces symmetrical to LiDAR HUD.

Target color encoding updated for helicopter radar mode, making classification display more intuitive.

🐛 Bug Fixes

Fixed an error in z-value calculation for the upper hemisphere sampling strategy (RDF_HemisphereSampleStrategy), causing some rays to deviate from the upper hemisphere.

Fixed degenerate results for the scanline sampling strategy (RDF_ScanlineSampleStrategy) under extreme parameters.

Fixed an issue where m_DisplayRange was unexpectedly covered by the AutoRunner range when LiDAR HUD was called independently.

📚 Documentation
Added RADAR_API.md (complete radar API reference), RADAR_TUTORIAL.md (14-section usage tutorial), and CHANGELOG.md; cleaned up all internal planning documents, retaining only reference materials for developers.

⚠️ The radar module and demo are still under development and should not be used in production environments!!! They will remain in the early development stage for a long time and are currently completely unstable and unusable. The LiDAR module is relatively stable.

Repository: https://github.com/ViVi141/Radar-Development-Framework | Contact: [email protected]

0.5.3

Fixes: Fixed the occlusion behavior of background quadrilaterals in visualization, ensuring correct background rendering in "point cloud only" mode; optimized the flag settings for debugging shapes, fixing the issue where in some cases the scan was paused but the visualization remained in the last frame and had not been cleared.

0.5.2

## 2026-02-18 — Network: Single-chip scan payload changed to reliable RPC (minor fix)

Overview: Changed the RPC channel for single-chip scan payloads from unreliable to reliable to reduce the probability of small (unfragmented) CSV payloads being lost at the transport layer. This change only alters the transport channel; RPC signatures and fragmentation logic remain unchanged.

Major Changes:

- Fix: `RpcDo_ScanCompleteWithPayload(string csv)` changed from `RplChannel.Unreliable` to `RplChannel.Reliable`.

- File: `scripts/Game/RDF/Lidar/Network/RDF_LidarNetworkComponent.c`

- Compatibility: Signature unchanged; no impact on external callers.

Test recommendations:

- Trigger `RequestScan()` and confirm on the client that `HasSyncedSamples()` returns true; verify the improved receive rate of a single payload in a simulated packet loss environment.

0.5.1

## 2026-02-17 — CSV/Export and Network Transfer Improvements (Minor Performance and Robustness Enhancements)

Overview: This update focuses on server-side CSV serialization, network transfer, and export paths, aiming to reduce peak memory/CPU usage and lower network sharding failure rates when processing large point clouds. All changes are backward-compatible implementation-level optimizations (no modification to public API signatures).

Major Changes (Actual Implementation):

- Optimization: **Caches and reuses** `RDF_LidarScanner` in `RDF_LidarNetworkComponent` (replacing each `new RDF_LidarScanner()`), reducing short-lifecycle object allocation and lowering GC pressure.

- File: `scripts/Game/RDF/Lidar/Network/RDF_LidarNetworkComponent.c`

- Optimization: Introduced CSV "parts" built per sample (add `RDF_LidarExport.SamplesToCSVParts`), and sends RPC payloads **streaming/chunking** on the server side. For larger payloads, it still supports merging parts and performing RLE compression before sending (retaining the original `RLE:` protocol prefix). This change significantly reduces the memory spikes caused by building massive strings all at once for large scans.

- Files: `scripts/Game/RDF/Lidar/Util/RDF_LidarExport.c`, `scripts/Game/RDF/Lidar/Network/RDF_LidarNetworkComponent.c`

- Improvement: `ExportToFile` now uses **best-effort atomic writing** (writing to a temporary `.tmp` file first, then the target file) to reduce the probability of truncated files during export (Note: the engine script cannot guarantee completely atomic renaming).

- File: `scripts/Game/RDF/Lidar/Util/RDF_LidarExport.c`

- Robustness Enhancement: Added optional logging (controlled by `m_Verbose`) for parsing failures/empty results in the RPC receive and fragment assembly paths, facilitating the diagnosis of network corruption or compression/decompression issues.

- File: `scripts/Game/RDF/Lidar/Network/RDF_LidarNetworkComponent.c`

Compatibility Notes:

- No changes have been made to the signatures or externally visible behavior of any public methods; the string format of CSV/RLE is compatible with client-side parsing (only the serialization/sharding implementation has been changed on the server side).

Testing Recommendations:

- Trigger a large ray count scan (e.g., m_RayCount >= 4096) locally or on the server to verify that memory/GC peaks, network sharding, and client-side parsing are normal; enable `m_Verbose` to view RPC parsing warning logs.

- Use `ExportToFile` to verify that the temporary file write path matches the final target file content (note the script-level renaming/deletion restrictions).

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0.5.0

A batch mesh rendering option has been added to improve performance at high ray counts. Related documentation and demo configurations have been updated to reflect this change. The default setting remains disabled to avoid impacting production mode.

0.4.4

The documentation has been updated, with the addition of English translations and module layout instructions to enhance the readability and maintainability of the developer guide.

0.4.3

Improved the network robustness of the LiDAR module, ensuring that network API availability is verified and expired references are cleaned up before use. Updated the `GetLastSamples()` method to return a defensive copy, preventing external modifications from affecting the visualizer's internal state. Related documentation has been updated accordingly.

0.4.2

The LiDAR module has been fixed and optimized, with unified use of local range variables to reduce temporary object allocation, optimized network serialization logic, improved fragment reception and assembly efficiency, adjusted asynchronous scheduling strategy, and pre-allocated rendering arrays to reduce memory jitter.

激光雷达模块已修复和优化，统一使用局部范围变量来减少临时对象分配，优化了网络序列化逻辑，提高了片段接收和组装效率，调整了异步调度策略，并预分配了渲染数组以减少内存抖动。

0.4.1

Example of LiDAR vehicles: https://reforger.armaplatform.com/workshop/6896E11A7CBD40B1-ExampleofLiDARvehicles

0.4.0

1) 64bea0e — 2026-02-12 🔧
Subject: Refactored LiDAR ray counting processing, removing the previous upper limit and ensuring a minimum of 1.

Impact: Improved scan configurability and accuracy (no longer limited by the old upper limit), while avoiding invalid configurations with 0 rays; demo and network-related behaviors have been adjusted accordingly.

2) cadd6e8 — 2026-02-12 🔧
Subject: Refactored file mode handling in export logic to improve readability and maintainability.

Impact: No major changes to functional behavior; code structure is clearer; regression testing to verify export compatibility is recommended.

0.3.1

Enhanced LiDAR network components include the addition of a last scan timestamp and synchronized sample checks to improve data validity and reliability.

0.3.0

Enhanced network synchronization capabilities of the LiDAR module, adding new network APIs and components to support reliable transmission in server-authoritative architectures and high-ray-count scenarios. The API has been refactored to introduce asynchronous scanning functionality. Demo configuration has been optimized to support point cloud-only mode; CSV import and export have been improved, enhancing serialization and compression efficiency. Documentation has been updated to include change notes, migration guides, and networked LiDAR sample code, and the scanner and visualization logic have been optimized.

0.2.1

Disable bootstrap feature in LiDAR demo to prevent automatic startup, ensuring better control over demo initialization.

0.2.0

1.Enhance LiDAR demo functionality by enabling auto-start, adding new sweep sampling strategy, and implementing scan completion callbacks. Update README and API documentation to reflect new features, including CSV export options and visualization settings for debugging. 
2.Improve demo configuration with verbose output and origin axis drawing for better clarity during testing.Implement point cloud rendering options in LiDAR demo, allowing users to toggle between game view with point cloud and point cloud only. Update related API methods and documentation to reflect these changes, including new settings for rendering behavior and background handling.

0.1.2

The LiDAR demo module has been integrated, the API entry point and configuration method have been unified, the separate demo class has been removed, a new preset factory method has been added, the startup and strategy cycling functions have been optimized, and the documentation has been updated to reflect the new structure and usage. The global auto-start feature in the LiDAR demo module and the refactor strategy cycling have been improved to utilize a new configuration method for improved clarity and functionality.

0.1.1

FIX DESC

0.1.0