Electromagnetic Wave Reradiation TRIZ Cases

Lever linkages shift a vehicle sensor holder away from lateral, corner, and vertical impact loads, then restore its operating position.

Real-time pixel background sensing adjusts TOF LiDAR field of view and readout thresholds to cut false alarms and improve ranging.

Outer-edge bias electrodes suppress charge pockets in a photonic mixer, improving demodulation speed while preserving quantum efficiency.

Stacked APD gain units flatten temperature-driven gain shifts, reducing dark current and improving laser radar signal stability.

Modular sensor assemblies combine essential and backup cameras, LiDAR, radar, and GNSS to sustain 360-degree perception during failures.

Filters, adaptive matching, and shutter control protect LIDAR from external light that can cause detector damage or false object detection.

LIDAR point clouds build a 3D view of ground, curbs, and obstacles so drivers can judge drivable areas in darkness, rain, or fog.

Alternating semiconductor regions widen the depletion layer to speed charge detection, improve responsivity, and reduce lidar timing jitter.

Calibration light and timing sweep let a gating camera correct emission-exposure offsets without dedicated hardware or lost imaging pixels.

Correlation-based superpixels adapt lidar pixel regions to reduce blurring and improve range accuracy, intensity precision, and object detection.

A graded semiconductor region extends depletion depth while speeding charge detection, improving responsivity and TOF lidar accuracy.

Combining external ground truth with sensor performance data improves ego vehicle sensor blockage detection under changing environmental conditions.

Backside illumination and isolated light-receiving regions improve CAPD pixel sensitivity, suppress noise, and support more accurate ranging.

Light blocking at MLA and PDA distal ends suppresses stray light in lidar photodetectors, improving point cloud accuracy and reducing false detections.

An adaptive optical shutter narrows receiver field of view to cut ambient light noise and extend solid-state LiDAR range within eye safety limits.

A delayed, attenuated secondary APD helps LiDAR recover hidden multi-return pulses when the primary detector is saturated.

Sector-based Bayesian statistics detect sensor blockages and range limits in real time with lower compute and no labeled training data.

Mirror-mounted LIDAR, radar, and cameras give large autonomous vehicles wider coverage with simpler installation and self-referenced calibration.

Relocating the scanning lidar and heat sink into the connecting arm cuts sensor pod moment, size, and weight while preserving cooling.

Detector bias control and pulsed laser arrays cut receiver noise, improving long-range LiDAR SNR without high-power lasers or moving scanners.

A mixed-aperture SPAD array switches photon data by light intensity to curb DToF pile-up and keep close-range distance readings accurate.

A graph neural network separates direct and multipath radar returns, converting indirect points into corrected object locations for autonomous driving.

Binary-coded single-photon detection improves LiDAR time-of-flight accuracy and noise rejection for low-power autonomous vehicle ranging.

Optical grating beam steering replaces moving LIDAR parts, enabling reliable, low-cost road debris detection with wide-angle scanning.

Frequency- and phase-modulated beams with grating couplers improve LiDAR range and velocity detection while reducing interference and noise.

One SPAD sensor switches between direct and indirect ToF modes to extend distance range while avoiding the scale and cost of multiple sensors.

Ultrasonic transducers vibrate the lidar window to remove debris on demand, maintaining clear line of sight without manual cleaning.

Interlaced scan lines and pixels improve LiDAR distance precision and wide-field coverage without excessive scan time or scanner complexity.

Radial velocity from coherent LiDAR separates nearby moving objects within one frame, improving point cloud tracking for autonomous vehicles.

Longitudinal motion gives close-object reflections a Doppler shift, helping lidar separate real targets from internal artifacts.

Normal covariance filtering improves ICP-based LIDAR point cloud merging by rejecting poor point pairs and sharpening transformation estimation.

Different receiver resolutions and fields of view let a rotating LiDAR detect nearby and distant objects with lower power and sensor cost.

Combining pulses from multiple light-receiving sections with time-division counting improves distance measurement accuracy while limiting processing load.

By merging the light source with the scanner reflector, this LiDAR layout cuts parts, removes reception blockage, and extends detection range.

Echo sample analysis detects LIDAR degradation from dirt, weather, or faults and triggers alerts or maintenance for safer autonomous driving.

Laser power is adjusted by vehicle speed and position to maintain object detection range while cutting energy use and interference.

Multiple-return lidar pulses are clustered by first reflections to flag phantom targets from homogeneous reflective surfaces in vehicle scans.

Temporal pulse coding separates aliased LiDAR reflections to extend measurable range and remove dead zones without longer measurement time.

Traffic-aware sensor switching cuts unnecessary vehicle sensor power use, helping extend EV range while maintaining detection coverage.

Sensors extend in self-driving scenarios to widen truck perception, then retract to cut drag, protect hardware, and improve fuel economy.

Adaptive detector biasing and selective laser-detector activation improve LiDAR SNR and range under Class 1 eye-safe power limits.

Light-sensor and timing-circuit detection tracks Lidar cross-talk sources, helping autonomous vehicles filter noise and improve perception.

A modular sensor pod with standardized ports enables hot-swapping and fast vehicle sensor suite upgrades without redesigning the base vehicle.

A global clock resets SPADs and charge-sharing DRAM cells cut pixel memory area and power in direct time-of-flight LiDAR.

Alternating donor and acceptor regions stabilize deep well potential gradients, improving signal charge collection, quantum efficiency, and noise control.

Adaptive truck sensors extend only when needed to widen field of view, cut blind spots, and avoid drag during autonomous driving.

RLS-based cluster velocity estimation improves RADAR object tracking in clutter, enabling accurate association and efficient linear Kalman updates.

Time-varying pulse dithering and multiple range hypotheses help LIDAR disambiguate aliased echoes and detect objects beyond nominal range.

Segmented radar, ultrasonic, and LiDAR sensing supports route updates, stability control, and dynamic object detection in autonomous-ready vehicles.

Switching non-measurement pixels out of multiplication mode cuts background-light power draw while preserving LiDAR distance sensing.