Radio Wave Reradiation/Reflection TRIZ Cases

Fast-Chirp FMCW radar estimates road height from elevation spectrum and backscattering, improving profile accuracy for vehicle control.

Hyper-local submaps, loop detection, and multi-view ICP improve autonomous vehicle radar pose estimation from sparse, noisy scans.

Mixed normal distribution modeling of radar reflections cuts training data needs while improving vehicle object recognition in complex environments.

Rotating ground reflectors modulate onboard radar returns to deliver precise bearing guidance for small landing areas when GPS is unreliable.

Multi-stage radar point-cloud filtering combines tracking, outlier removal, and velocity modeling to separate dynamic objects for more reliable ego-motion estimation.

Non-uniform FMCW chirps vary timing and frequency to improve range resolution, extend detectable velocity, and reduce Doppler ambiguity.

Modular reflector panels with linear and tilt adjustment enable precise SAR validation while easing transport, setup, and subsidence simulation.

Peak shifts across chirp frequency bands help distinguish stationary objects from multipath reflections, improving radar distance accuracy.

Rotational on-system calibration builds a correction matrix for cross-coupling, gain-phase variation, and nodal misalignment in radar arrays.

Distributed sampling across physical chirps forms virtual chirps, simplifying long-range, high-speed radar range and radial velocity measurement.

Distributed transceiver units send digitized time signals to a central evaluator, improving angular resolution without excessive radar processing cost.

Adaptive Doppler filtering and clutter maps help mmWave radar distinguish human targets from rain or snow and reduce false door activations.

Flat-plate measurements at multiple positions reduce bistatic sidelobe errors and improve radar azimuth calibration accuracy.

Suction-cup anchoring lets a portable calibration mount attach to a support vehicle for precise ADAS sensor setup outside service centers.

Multiple radar antennas with overlapping front, rear, and side beams expand vehicle object detection in intersections and other complex traffic scenes.

Multiple radar chips generate separate data cubes that a central processor fuses to extend detection range and sharpen angle estimation.

Peak detection in stationary-target velocity ratios corrects ego speed despite radar mounting errors and changing target density.

Single-scan radar detections are used to locate a target vehicle’s center of rotation and estimate yaw-rate with lower computational burden.

Using vehicle dynamics and radar range-rate compensation, this case identifies stationary and moving objects accurately during turns with lower compute load.

Adjustable phase shifting and power combining let MIMO radar support more antennas without adding costly receiver channels.

Raw radar detections are combined with geometric estimation to derive a target vehicle's yaw rate and OTG velocity in real time.

Radar-reflective road markings and signs strengthen returns through rain, snow, and fog for reliable lane guidance and vehicle control.

A spaced reflector redirects radar beams and echoes beyond the sensor's native view, extending lateral coverage without extra sensors.

Assigning radar frequency, coding, and time windows by vehicle position and orientation cuts interference while reusing limited operating ranges.

Radar, ADS-B, AIS, C-UAS, and RemoteID fusion helps remote pilots detect intruders and monitor surveillance degradation during BVLOS operations.

Synthetic aperture radar turns robot motion into a virtual antenna array, improving obstacle localization without multi-antenna complexity.

Real-time SODAR wind sensing and pseudolite positioning let a UAV adjust glide slope, descent, and turns for automated landing in high winds.

A single moving radar sensor builds a synthetic aperture image to localize obstacles accurately and guide path changes in complex environments.

Coordinated subband and time-slot allocation helps warehouse vehicle radars avoid mutual interference and improve detection reliability.

Radar-based stationary scatterer detection improves low-speed and stationary vehicle velocity estimation beyond noisy GPS and inertial sensors.

Multi-sensor radar integrates duplicate detections and hands off object data between sensor fields for continuous, reliable vehicle tracking.

Converts 1D Doppler radar data into 2D object velocity and yaw rate using regression, weighting, and outlier rejection for better tracking.

By switching between Doppler and FMCW modes, this portable radar balances through-obstacle detection, target accuracy, and power use.

Energy-based listen-before-talk timing helps radar avoid occupied RF channels, reducing false target detections and wasted processing.

Deconvolved pulse returns and time-gating help measure low-signature radar cross sections accurately in RFI-prone test ranges.

Periodic positive-negative Doppler energy differences reveal swaying objects, helping radar filter clutter and cut unnecessary processing.

Robust filtering, IMU fusion, and local map matching improve 4D radar localization when sparse point clouds and weather noise limit precision.

Using virtual channels and weighted partial arrays, this case cuts side lobes and enables sparse MIMO radar target localization.

Alternating two FMCW center frequencies uses phase differences and Doppler shift gaps to resolve velocity ambiguity and improve radar range-velocity estimation.

A 3D sensor and GPS map trunks and poles ahead of the vehicle, triggering timely weeding tool retraction to avoid crop damage.

Calibration is derived from scene measurements by optimizing a parameter-dependent representation, enabling robust radar tuning without reference targets.

Phase-shifted ultrasonic arrays adapt detection zones to vehicle travel direction, improving object localization and reducing false echoes.

Multiple radar units co-register overlapping FoVs and use vehicle motion to synthesize a larger aperture for sharper angular resolution.

Coordinated wireless devices share radar transmit and receive roles to extend range and improve resolution without dedicated radar hardware.

By switching automotive radar between active and passive modes, vehicles can use other cars' signals to cut cross-radar interference.

Opposite circular polarizations enable two-way antenna ranging that compensates for LOS rotation and metal reflections for sub-millimeter accuracy.

Coherence sub-band summation and MIMO channel estimation suppress antenna coupling, separate buried depths, and cut false alarms.

Radar data from an object moved along the vehicle axis is used to detect azimuth and elevation misalignment without costly mechanical tools.

Radar speed correction is adjusted by classifying road objects and upper objects, improving vehicle speed accuracy despite coarse vertical angle resolution.

Vector histogram indexing stores all radar return amplitudes without threshold tests, preserving weak target data while stabilizing processing load.

A radar system compensates flight path deviations using terrain elevation data and Taylor series expansion to correct phase errors in SAR imagery.

Varying pulse repetition frequencies enables a radar device to identify and remove multi-order echoes without increasing processing circuit complexity.

Phased-array radars estimate attitude stability using radar cross-section statistics at varying elevation angles.

A synthetic aperture radar signal analysis device clusters stable reflection points and performs vector synthesis of displacement rates.

A radar signal processor corrects reception data using reference angular positions to resolve phase and power errors in automotive detection systems.

Classifies aircraft behavior using identification data and position tracking to detect anomalies.

Dynamic beam width control reduces interrogation rates while maintaining precise azimuth positioning for aircraft targets.

A radially-polarized probe transmits microwave signals with dynamic polarization to detect targets in samples.

A handheld MTI radar sensor quantifies radial platform motion using frequency domain phase data from large stationary objects.